PREFIX kisao: PREFIX rdf: PREFIX rdfs: PREFIX xsd: kisao:KISAO_0000632 a rdfs:Class ; rdfs:label "functional iteration root-finding method"@en ; rdfs:comment """Iterative method for finding the root of a function f(x) given by y^{n(m+1)} = h_{n} β_{n,0} f(t_{n}, y^{n(m)}) + a_n This method only involves evaluations of f. This method is suitable for non-stiff functions."""@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000631 . kisao:KISAO_0000245 a rdf:Property ; rdfs:label "has characteristic"@en ; rdfs:comment "'has characteristic' links algorithms to the characteristics they possess."@en ; rdfs:domain kisao:KISAO_0000000 ; rdfs:range kisao:KISAO_0000097 . kisao:KISAO_0000259 a rdf:Property ; rdfs:label "has parameter"@en ; rdfs:comment "'has parameter' links algorithms to the parameters they use."@en ; rdfs:domain kisao:KISAO_0000000 ; rdfs:range kisao:KISAO_0000201 . kisao:KISAO_0000360 a rdf:Property ; rdfs:label "uses"@en ; rdfs:comment "A relation between algorithms indicating that one algorithm uses another one (for example, if the algorithm switches between several algorithms)."@en ; rdfs:domain kisao:KISAO_0000000 ; rdfs:range kisao:KISAO_0000000 . kisao:KISAO_0000361 a rdf:Property ; rdfs:label "is generalization of"@en ; rdfs:comment "A relation between kinetic simulation algorithms, indicating that one is a generalization of another (e.g.if one extends another to suit systems with more general characteristics )."@en ; rdfs:domain kisao:KISAO_0000000 ; rdfs:range kisao:KISAO_0000000 ; rdfs:subPropertyOf kisao:KISAO_0000359 . kisao:KISAO_0000857 a rdfs:Class ; rdfs:label "median"@en ; rdfs:comment "The median of a set of values. If the values contain NaN the median is NaN."@en ; rdfs:subClassOf kisao:KISAO_0000824 . kisao:KISAO_0000323 a rdfs:Class ; rdfs:label "equation-free probabilistic steady-state approximation"@en ; rdfs:comment """We present a probabilistic steady-state approximation that separates the time scales of an arbitrary reaction network, detects the convergence of a marginal distribution to a quasi-steady-state, directly samples the underlying distribution, and uses those samples to accurately predict the state of the system, including the effects of the slow dynamics, at future times. The numerical method produces an accurate solution of both the fast and slow reaction dynamics while, for stiff systems, reducing the computational time by orders of magnitude. The developed theory makes no approximations on the shape or form of the underlying steady-state distribution and only assumes that it is ergodic. <...> The developed theory may be applied to any type of kinetic Monte Carlo simulation to more efficiently simulate dynamically stiff systems, including existing exact, approximate, or hybrid stochastic simulation techniques. """@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000333 . kisao:KISAO_0000359 a rdf:Property ; rdfs:label "is similar to"@en ; rdfs:comment "A relationship indicating that two entities are similar to each other."@en ; rdfs:range . kisao:KISAO_0000656 a rdfs:Class ; rdfs:label "use adaptive time steps"@en ; rdfs:comment "Whether an algorithm should use adaptive or fixed time steps."@en ; rdfs:subClassOf kisao:KISAO_0000243 . kisao:KISAO_0000250 a rdf:Property ; rdfs:label "is parameter of"@en ; rdfs:comment "'is parameter of' is an inverse of 'has parameter' and links parameters to the algorithms which use them."@en ; rdfs:domain kisao:KISAO_0000201 ; rdfs:range kisao:KISAO_0000000 , kisao:KISAO_0000231 , kisao:KISAO_0000408 , kisao:KISAO_0000323 , kisao:KISAO_0000057 , kisao:KISAO_0000331 , kisao:KISAO_0000074 , kisao:KISAO_0000045 , kisao:KISAO_0000418 , kisao:KISAO_0000423 , kisao:KISAO_0000417 , kisao:KISAO_0000084 , kisao:KISAO_0000039 . kisao:KISAO_0000251 a rdf:Property ; rdfs:label "has type"@en ; rdfs:comment "Indicates the type of algorithm parameter value, such as, for example, xsd:double for 'absolute tolerance'."@en ; rdfs:domain kisao:KISAO_0000201 ; rdfs:range . kisao:KISAO_0000828 a rdfs:Class ; rdfs:label "maximum ignoring NaN"@en ; rdfs:comment "The maximum value of a set of values, ignoring NaN entries."@en ; rdfs:subClassOf kisao:KISAO_0000824 . kisao:KISAO_0000556 a rdfs:Class ; rdfs:label "relative quadrature tolerance"@en ; rdfs:comment "Relative error tolerance of the adjoint solution."@en ; rdfs:subClassOf kisao:KISAO_0000209 . kisao:KISAO_0000814 a rdfs:Class ; rdfs:label "flux control coefficient matrix (unscaled)"@en ; rdfs:comment "The unscaled flux control coefficient matrix. The dimensions are reactions by reactions."@en ; rdfs:subClassOf kisao:KISAO_0000800 . kisao:KISAO_0000850 a rdfs:Class ; rdfs:label "cumulative product ignoring NaN"@en ; rdfs:comment "The cumulative product of a set of values, ignoring Nan entries."@en ; rdfs:subClassOf kisao:KISAO_0000824 . kisao:KISAO_0000667 a rdfs:Class ; rdfs:label "memory size"@en ; rdfs:comment "Maximum number of points to store in memory, such as in the second order backward implicit product Euler scheme."@en ; rdfs:subClassOf kisao:KISAO_0000242 . kisao:KISAO_0000681 a rdfs:Class ; rdfs:label "maximum time"@en ; rdfs:comment "Maximum amount of wall time for an operation."@en ; rdfs:subClassOf kisao:KISAO_0000244 . kisao:KISAO_0000567 a rdfs:Class ; rdfs:label "force physical correctness"@en ; rdfs:comment "Indicates whether to force physical correctness."@en ; rdfs:subClassOf kisao:KISAO_0000243 . kisao:KISAO_0000452 a rdfs:Class ; rdfs:label "random updating policy"@en ; rdfs:comment "An updating policy that chooses a transition randomly."@en ; rdfs:subClassOf kisao:KISAO_0000451 . kisao:KISAO_0000268 a rdf:Property ; rdfs:label "is characteristic of"@en ; rdfs:comment "'is characteristic of' is an inverse of 'has characteristic' and links characteristics to the algorithms which possess them."@en ; rdfs:domain kisao:KISAO_0000097 ; rdfs:range kisao:KISAO_0000000 . kisao:KISAO_0000470 a rdfs:Class ; rdfs:label "optimization algorithm"@en ; rdfs:comment "An optimization algorithm tries to find the minumum or maximum of an arbitrary function. It takes a function of one or several variables and determines the values for the variables so that the function value is optimal."@en ; rdfs:seeAlso , ; rdfs:subClassOf kisao:KISAO_0000000 . kisao:KISAO_0000021 a rdfs:Class ; rdfs:label "StochSim nearest-neighbour algorithm"@en ; rdfs:comment "The nearest-neighbour algorithm allows for the representation of spatial information, by adding a two-dimensional lattice in the form of a probabilistic cellular automata. That way, nearest neighbour interactions do additionally influence reactions taking place in the systems. Reactions between entities are calculated using the agent-based simulation algorithm [http://identifiers.org/biomodels.kisao/KISAO_0000017]."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000363 . kisao:KISAO_0000232 a rdfs:Class ; rdfs:label "LSOIBT"@en ; rdfs:comment "LSOIBT solves linearly implicit systems in which the matrices involved are all assumed to be block-tridiagonal. Linear systems are solved by the LU method."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000094 . kisao:KISAO_0000017 a rdfs:Class ; rdfs:label "multi-state agent-based simulation method"@en ; rdfs:comment "The agent-based simulation method instantiates each molecule as an individual software object. The interactions between those objects are determined by interaction probabilities according to experimental data. The probability is depended on the state the molecule is in at that specific time (molecules have multiple-state). Additionally, ''pseudo-molecules'' are introduced to the system in order to simulate unimolecular reactions. For simulation, continuous time is broken down into discrete, independent ''slices''. During each time slice one molecule is selected randomly, a second molecule or pseudo-molecule is selected afterwards (leading to either a unimolecular or a bimolecular reaction). The reaction will only take place if a produced random number exceeds the reaction probability calculated beforehand. In that case, the system is updated after that reaction."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000363 . kisao:KISAO_0000603 a rdfs:Class ; rdfs:label "minimum reaction rate for continuous approximation"@en ; rdfs:comment "Minimum reaction rate required for approximation as a continuous Markov process."@en ; rdfs:subClassOf kisao:KISAO_0000244 . kisao:KISAO_0000040 a rdfs:Class ; rdfs:label "Poisson tau-leaping method"@en ; rdfs:comment "Explicit tau-leaping method with basic pre leap check."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000039 . kisao:KISAO_0000513 a rdfs:Class ; rdfs:label "NL2SOL"@en ; rdfs:comment "The NL2SOL method is based on an adaptive nonlinear least-squares algorithm, devised by Dennis and colleagues. For problems with large number of residuals, this algorithm is known to be more reliable than Gauss-Newton or Levenberg-Marquardt method and more efficient than the secant or variable metric algorithms that are intended for general function minimization."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000471 . kisao:KISAO_0000643 a rdfs:Class ; rdfs:label "upper bound"@en ; rdfs:comment "An upper bound on an estimate of a quantity."@en ; rdfs:subClassOf kisao:KISAO_0000641 . kisao:KISAO_0000482 a rdfs:Class ; rdfs:label "half-bandwith parameter"@en ; rdfs:comment "the parameter related to the half-bandwidth value used by the Banded linear solver or preconditioner."@en ; rdfs:subClassOf kisao:KISAO_0000201 . kisao:KISAO_0000301 a rdfs:Class ; rdfs:label "Heun method"@en ; rdfs:comment "The method is named after Karl L. W. M. Heun and is a numerical procedure for solving ordinary differential equations (ODEs) with a given initial value. It can be seen as extension of the Euler method [http://identifiers.org/biomodels.kisao/KISAO_0000261] into two-stage second-order Runge-Kutta method."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000064 . kisao:KISAO_0000275 a rdf:Property ; rdfs:label "has Runge-Kutta method order"@en ; rdfs:comment "Indicates the order of a 'Runge-Kutta based method' [urn.miriam.biomodels.kisao:KISAO_0000064]. A 'Runge-Kutta based method' has order p if for sufficiently smooth initial value problems (y'=f(x,y), y(x0)=y0), ||y(x0 + h)-y1||<=Kh^(p+h)."@en ; rdfs:domain kisao:KISAO_0000064 ; rdfs:range xsd:int . kisao:KISAO_0000094 a rdfs:Class ; rdfs:label "Livermore solver"@en ; rdfs:comment "Method to solve ordinary differential equations developed at the Lawrence Livermore National Laboratory."@en ; rdfs:subClassOf kisao:KISAO_0000694 . kisao:KISAO_0000203 a rdfs:Class ; rdfs:label "particle number lower limit"@en ; rdfs:comment "This parameter of 'Pahle hybrid method' [http://identifiers.org/biomodels.kisao/KISAO_0000231] is a double value specifying the lower limit for particle numbers. Species with a particle number below this value are considered as having a low particle number. The 'particle number lower limit' cannot be higher than the 'particle number upper limit' [http://identifiers.org/biomodels.kisao/KISAO_0000204]."@en ; rdfs:subClassOf kisao:KISAO_0000252 . kisao:KISAO_0000610 a rdfs:Class ; rdfs:label "composite-rejection stochastic simulation algorithm"@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000333 . kisao:KISAO_0000692 a rdfs:Class ; rdfs:label "cellular system"@en ; rdfs:subClassOf kisao:KISAO_0000690 . kisao:KISAO_0000283 a rdfs:Class ; rdfs:label "IDA"@en ; rdfs:comment """IDA solves real differential-algebraic systems in N-space, in the general form F(t,y,y')=0, y(t0)=y0, y'(t0)=y'0. At each step, a Newton iteration [http://identifiers.org/biomodels.kisao/KISAO_0000408] leads to linear systems Jx=b, which are solved by one of five methods - two direct (dense or band; serial version only) and three Krylov [http://identifiers.org/biomodels.kisao/KISAO_0000354] (GMRES [http://identifiers.org/biomodels.kisao/KISAO_0000353], BiCGStab [http://identifiers.org/biomodels.kisao/KISAO_0000392], or TFQMR [http://identifiers.org/biomodels.kisao/KISAO_0000396]). IDA is written in C, but derived from the package DASPK [http://identifiers.org/biomodels.kisao/KISAO_0000355] which is written in Fortran."""@en ; rdfs:seeAlso , , ; rdfs:subClassOf kisao:KISAO_0000432 . kisao:KISAO_0000836 a rdfs:Class ; rdfs:label "amount"@en ; rdfs:comment "The extensive quantity amount."@en ; rdfs:subClassOf kisao:KISAO_0000831 . kisao:KISAO_0000355 a rdfs:Class ; rdfs:label "DASPK"@en ; rdfs:comment """In DASPK, we have combined the time-stepping methods of DASSL [http://identifiers.org/biomodels.kisao/KISAO_0000255] with preconditioned iterative method GMRES [http://identifiers.org/biomodels.kisao/KISAO_0000386], for solving large-scale systems of DAEs of the form F(t, y, y') = 0, where F, y, y' are N-dimensional vectors, and a consistent set of initial conditions y(t0) = y0, y'(t0) = y'0 is given. DASPK is written in Fortran."""@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000432 . kisao:KISAO_0000427 a rdfs:Class ; rdfs:label "number of clusters"@en ; rdfs:comment "Parameter specifying the number of clusters used by C-means algorithm."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000429 . kisao:KISAO_0000845 a rdfs:Class ; rdfs:label "sum"@en ; rdfs:comment "The sum of a set of values. If the values contain NaN the sum is NaN."@en ; rdfs:subClassOf kisao:KISAO_0000824 . kisao:KISAO_0000524 a rdfs:Class ; rdfs:label "partitioned leaping method"@en ; rdfs:comment "Multiscale simulation approach for modeling stochasticity in chemical reaction networks. The approach seamlessly integrates exact-stochastic and \"leaping\" methodologies into a single partitioned leaping algorithmic framework. The technique correctly accounts for stochastic noise at significantly reduced computational cost, requires the definition of only three modelindependent parameters and is particularly well-suited for simulating systems containing widely disparate species populations."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000039 . kisao:KISAO_0000659 a rdfs:Class ; rdfs:label "Naldi MDD logical model stable state search method"@en ; rdfs:comment "Efficient method for determining the stable states of a regulatory graph using a Multi-valued Decision Diagram (MDD) representation of the logical functions."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000660 . kisao:KISAO_0000821 a rdfs:Class ; rdfs:label "intensive property"@en ; rdfs:comment "An intensive variable such as a concentration or temperature."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000820 . kisao:KISAO_0000381 a rdfs:Class ; rdfs:label "midpoint method"@en ; rdfs:comment "The midpoint method is an explicit method for approximating the solution of the initial value problem y' = f(x,y); y(x0) = y0 at x for a given step size h. For the midpoint method the derivative of y(x) is approximated by the symmetric difference y'(x) = ( y(x+h) - y(x-h) ) / 2h + O(h2)."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000064 . kisao:KISAO_0000370 a rdfs:Class ; rdfs:label "type of problem"@en ; rdfs:comment "A characteristic describing the type of the problems which can be solved by the algorithm."@en ; rdfs:subClassOf kisao:KISAO_0000097 . kisao:KISAO_0000396 a rdfs:Class ; rdfs:label "transpose-free quasi-minimal residual algorithm"@en ; rdfs:comment """A version of CGS [http://identifiers.org/biomodels.kisao/KISAO_0000393] which 'quasi-minimizes' the residual in the space spanned by the vectors generated by the CGS iteration. """@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000389 . kisao:KISAO_0000333 a rdfs:Class ; rdfs:label "accelerated stochastic simulation algorithm"@en ; rdfs:comment "An algorithm, which accelerates SSA [http://identifiers.org/biomodels.kisao/KISAO_0000029] either at the expense of its accuracy or exact."@en ; rdfs:subClassOf kisao:KISAO_0000241 . kisao:KISAO_0000287 a rdfs:Class ; rdfs:label "Milstein method"@en ; rdfs:comment "The Milstein method is a technique for the approximate numerical solution of a stochastic differential equation."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000697 . kisao:KISAO_0000392 a rdfs:Class ; rdfs:label "biconjugate gradient stabilized method"@en ; rdfs:comment "An iterative method for the numerical solution of nonsymmetric linear systems. It is a variant of the biconjugate gradient method (BiCG) [http://identifiers.org/biomodels.kisao/KISAO_0000358] and has faster and smoother convergence than the original BiCG."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000395 . kisao:KISAO_0000273 a rdfs:Class ; rdfs:label "hard-particle molecular dynamics"@en ; rdfs:comment "A collision-driven molecular dynamics algorithm for a system of non-spherical particles."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000000 . kisao:KISAO_0000380 a rdfs:Class ; rdfs:label "Richardson extrapolation based method"@en ; rdfs:comment "A method based on ideas of Richardson extrapolation, which is a process for obtaining increased accuracy in a discretized approximation by extrapolating results from coarse discretizations to an arbitrarily fine one."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000377 . kisao:KISAO_0000367 a rdfs:Class ; rdfs:label "partitioned Runge-Kutta method"@en ; rdfs:comment "If a Hamiltonian system possesses a natural partitioning, it is possible to integrate its certain components using one Runge-Kutta method and other components using a different Runge-Kutta method. The overall s-stage scheme is called a partitioned Runge-Kutta method."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000064 . kisao:KISAO_0000416 a rdfs:Class ; rdfs:label "partial least squares regression method"@en ; rdfs:comment "Multivariate regression method based on estimated latent variables. Related to Principal Component Analysis (PCA) and Principal Component Regression (PCR)."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000423 . kisao:KISAO_0000502 a rdfs:Class ; rdfs:label "DA-DFBA"@en ; rdfs:comment "Dynamic Flux Balance Analysis (DFBA) [http://identifiers.org/biomodels.kisao/KISAO_0000499] couples flux balance analysis (FBA) [http://identifiers.org/biomodels.kisao/KISAO_0000437] model approaches with dynamic model approaches. The direct approach (DA) includes the LP solver in the right-hand side evaluator for the ordinary differential equations (ODEs) and takes advantage of reliable implicit ODE integrators with adaptive step size for error control."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000499 . kisao:KISAO_0000246 a rdf:Property ; rdfs:label "is hybrid of"@en ; rdfs:comment """The basic idea of hybrid simulation methods is to combine the advantages of complementary simulation approaches: the whole system is subdivided into appropriate parts and different simulation methods operate on these parts at the same time. 'is hybrid of' is a relation between the complex simulation method and algorithms it applies to the different parts of the system."""@en ; rdfs:seeAlso ; rdfs:domain kisao:KISAO_0000000 ; rdfs:range kisao:KISAO_0000000 ; rdfs:subPropertyOf kisao:KISAO_0000360 . kisao:KISAO_0000236 a rdfs:Class ; rdfs:label "exact solution"@en ; rdfs:comment "Algorithm, possessing this characteristic, provides an exact solution to the initial problem."@en ; rdfs:subClassOf kisao:KISAO_0000235 . kisao:KISAO_0000492 a rdfs:Class ; rdfs:label "asynchronous updating policy"@en ; rdfs:comment "An updating policy where all enabled transitions (events) occur independently. Thus a state has as many successors as the number of transitions enabled in this state."@en ; rdfs:subClassOf kisao:KISAO_0000451 . kisao:KISAO_0000089 a rdfs:Class ; rdfs:label "LSODAR"@en ; rdfs:comment "LSODAR is a variant of LSODA [http://identifiers.org/biomodels.kisao/KISAO_0000088] with a root finding capability added. Thus it solves problems dy/dt = f with dense or banded Jacobian and automatic method selection, and at the same time, it finds the roots of any of a set of given functions of the form g(t,y). This is often useful for finding stop conditions, or for finding points at which a switch is to be made in the function f."@en ; rdfs:seeAlso , ; rdfs:subClassOf kisao:KISAO_0000094 . kisao:KISAO_0000039 a rdfs:Class ; rdfs:label "tau-leaping method"@en ; rdfs:comment "Approximate acceleration procedure of the stochastic simulation algorithm [http://identifiers.org/biomodels.kisao/KISAO_0000029] that divides the time into subintervals and ''leaps'' from one to another, firing all the reaction events in each subinterval."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000621 . kisao:KISAO_0000593 a rdfs:Class ; rdfs:label "MOMA"@en ; rdfs:comment "minimization of metabolic adjustment (MOMA) is an extension of FBA for the prediction of flux distributions in gene knockouts. MOMA identifies the closest point in the permissible flux space of the knockout to the wild-type flux vector by solving an optimization problem."@en ; rdfs:subClassOf kisao:KISAO_0000622 , kisao:KISAO_0000630 . kisao:KISAO_0000849 a rdfs:Class ; rdfs:label "cumulative sum"@en ; rdfs:comment "The cumulative sum of a set of values. If the values contain NaN the cumulative sum is NaN."@en ; rdfs:subClassOf kisao:KISAO_0000824 . kisao:KISAO_0000582 a rdfs:Class ; rdfs:label "Spatiocyte method"@en ; rdfs:comment "Lattice-based stochastic particle simulation method for biochemical reaction and diffusion processes."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000056 . kisao:KISAO_0000319 a rdfs:Class ; rdfs:label "Monte Carlo method"@en ; rdfs:comment "Monte Carlo methods (or Monte Carlo experiments) are a class of computational algorithms that rely on repeated random sampling to compute their results."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000000 . kisao:KISAO_0000244 a rdfs:Class ; rdfs:label "granularity control parameter"@en ; rdfs:comment "Parameter controlling granularity."@en ; rdfs:subClassOf kisao:KISAO_0000201 . kisao:KISAO_0000539 a rdfs:Class ; rdfs:label "minimum factor to change step size by"@en ; rdfs:comment "Minimum factor to increase/decrease step size by in one step. The new step-size is chosen subject to the restriction fac1 <= current step-size / old step-size <= fac2."@en ; rdfs:subClassOf kisao:KISAO_0000242 . kisao:KISAO_0000695 a rdfs:Class ; rdfs:label "parameters for"@en ; rdfs:comment "The children parameters of this term are applied when the parent general term is implented as the more-specific value of this term. For example: a 'parameters for' term might be used as a child of an 'ODE Solver' ([http://identifiers.org/biomodels.kisao/KISAO_0000694]), have a value of 'KISAO_0000019' (CVODE)', and have a child term 'use stiff method' of 'true' ([http://identifiers.org/biomodels.kisao/KISAO_0000671])"@en ; rdfs:subClassOf kisao:KISAO_0000201 . kisao:KISAO_0000678 a rdfs:Class ; rdfs:label "maximum number of steps for approximation"@en ; rdfs:comment "Maximum number of steps to take in approximating an analysis."@en ; rdfs:subClassOf kisao:KISAO_0000415 . kisao:KISAO_0000621 a rdfs:Class ; rdfs:label "stochastic simulation leaping method"@en ; rdfs:subClassOf kisao:KISAO_0000333 . kisao:KISAO_0000032 a rdfs:Class ; rdfs:label "explicit fourth-order Runge-Kutta method"@en ; rdfs:comment "The Runge-Kutta method is a method for the numerical integration of ODES with a given initial value. The calculation of the next integration step at time t+1 is based on the state of the system at time point t, plus the product of the size of the interval and an estimated slope. The slope is a weighted average of 4 single slope points (beginning of interval-midpoint-midpoint-end of interval)."@en ; rdfs:subClassOf kisao:KISAO_0000064 . kisao:KISAO_0000046 a rdfs:Class ; rdfs:label "trapezoidal tau-leaping method"@en ; rdfs:comment "Formula for accelerated discrete efficient stochastic simulation of chemically reacting system [which] has better accuracy and stiff stability properties than the explicit and implicit [http://identifiers.org/biomodels.kisao/KISAO_0000045] tau-leaping formulas for discrete stochastic systems, and it limits to the trapezoidal rule in the deterministic regime."@en ; rdfs:subClassOf kisao:KISAO_0000039 . kisao:KISAO_0000545 a rdfs:Class ; rdfs:label "include sensitivity variables in error control mechanism"@en ; rdfs:comment "Specifies whether sensitivity variables are included or not in the error control mechanism."@en ; rdfs:subClassOf kisao:KISAO_0000242 , kisao:KISAO_0000243 . kisao:KISAO_0000525 a rdfs:Class ; rdfs:label "stop condition"@en ; rdfs:comment "A condition upon which a simulation should terminate."@en ; rdfs:subClassOf kisao:KISAO_0000201 . kisao:KISAO_0000326 a rdfs:Class ; rdfs:label "number of samples"@en ; rdfs:comment "Parameter of 'equation-free probabilistic steady-state approximation' method [http://identifiers.org/biomodels.kisao/KISAO_0000323], which determines the number of samples taken from the distribution."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000242 . kisao:KISAO_0000825 a rdfs:Class ; rdfs:label "mean ignoring NaN"@en ; rdfs:comment "The mean (average) of a set of values, ignoring NaN entries."@en ; rdfs:subClassOf kisao:KISAO_0000824 . kisao:KISAO_0000832 a rdfs:Class ; rdfs:label "time"@en ; rdfs:comment "The implied time variable of the model state."@en ; rdfs:subClassOf kisao:KISAO_0000831 . kisao:KISAO_0000348 a rdfs:Class ; rdfs:label "extended finite element method"@en ; rdfs:comment "A numerical method to model arbitrary discontinuities in continuous bodies that does not require the mesh to conform to the discontinuities nor significant mesh refinement near singularities. In X-FEM the standard finite element approximation [http://identifiers.org/biomodels.kisao/KISAO_0000337] is enriched and the approximation space is extended by an additional family of functions."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000369 . kisao:KISAO_0000375 a rdfs:Class ; rdfs:label "delay differential equation problem"@en ; rdfs:subClassOf kisao:KISAO_0000405 . kisao:KISAO_0000356 a rdfs:Class ; rdfs:label "DASSL"@en ; rdfs:comment "DASSL is designed for the numerical solution of implicit systems of differential/algebraic equations written in the form F(t,y,y')=0, where F, y, and y' are vectors, and initial values for y and y' are given."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000432 . kisao:KISAO_0000571 a rdfs:Class ; rdfs:label "absolute tolerance adjustment factor"@en ; rdfs:comment "How much to adjust the absolute tolerance."@en ; rdfs:subClassOf kisao:KISAO_0000597 . kisao:KISAO_0000497 a rdfs:Class ; rdfs:label "KLU"@en ; rdfs:comment "KLU is a software package and an algorithm for solving sparse unsymmetric linear systems of equations that arise in circuit simulation applications. It relies on a permutation to Block Triangular Form (BTF), several methods for finding a fill-reducing ordering (variants of approximate minimum degree and nested dissection), and Gilbert/Peierls’ sparse left-looking LU factorization algorithm to factorize each block. The package is written in C and includes a MATLAB interface."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000000 . kisao:KISAO_0000680 a rdfs:Class ; rdfs:label "duration"@en ; rdfs:comment "Length of time to simulate."@en ; rdfs:subClassOf kisao:KISAO_0000201 . kisao:KISAO_0000449 a rdfs:Class ; rdfs:label "synchronous logical model simulation method"@en ; rdfs:comment "Qualitative (logical) models specify the evolution rules of their components. In the case of a synchronous updating all enabled transitions are processed simultaneously. "@en ; rdfs:subClassOf kisao:KISAO_0000448 . kisao:KISAO_0000393 a rdfs:Class ; rdfs:label "ingenious conjugate gradients-squared method"@en ; rdfs:comment "A Lanczos-type method for nonsymmetric sparse linear systems. The method is based on a polynomial variant of the conjugate gradients algorithm [http://identifiers.org/biomodels.kisao/KISAO_0000357]. Although related to the so-called bi-conjugate gradients (Bi-CG) algorithm [http://identifiers.org/biomodels.kisao/KISAO_0000358], it does not involve adjoint matrix-vector multiplications, and the expected convergence rate is about twice that of the Bi-CG algorithm."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000395 . kisao:KISAO_0000029 a rdfs:Class ; rdfs:label "Gillespie direct algorithm"@en ; rdfs:comment "Stochastic simulation algorithm using the reaction probability density function (next-reaction density function), giving the probability that the next reaction will happen in a given time interval. To choose the next reaction to fire, the algorithm directly and separately calculates the identity of the reaction and the time it will fire."@en ; rdfs:seeAlso , ; rdfs:subClassOf kisao:KISAO_0000241 . kisao:KISAO_0000057 a rdfs:Class ; rdfs:label "Brownian diffusion Smoluchowski method"@en ; rdfs:comment "In the Brownian diffusion Smoluchowski method, ''each molecule is treated as a point-like particle that diffuses freely in three-dimensional space. When a pair of reactive molecules collide, such as an enzyme and its substrate, a reaction occurs and the simulated reactants are replaced by products. [..] Analytic solutions are presented for some simulation parameters while others are calculated using look-up tables''. Supported chemical processes include molecular diffusion, treatment of surfaces, zeroth-order-, unimolecular-, and bimolecular reactions."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000056 . kisao:KISAO_0000802 a rdfs:Class ; rdfs:label "control coefficient (scaled)"@en ; rdfs:comment "A scaled control coefficient of any dependent element (such as a reaction or a floating species) with respect to an independent element (such as a global parameter or boundary species)."@en ; rdfs:subClassOf kisao:KISAO_0000800 . kisao:KISAO_0000622 a rdfs:Class ; rdfs:label "flux balance method"@en ; rdfs:subClassOf kisao:KISAO_0000685 . kisao:KISAO_0000553 a rdfs:Class ; rdfs:label "optimization solver"@en ; rdfs:comment "Optimization solver such as CPLEX, GLPK, or Gurobi."@en ; rdfs:subClassOf kisao:KISAO_0000243 . kisao:KISAO_0000662 a rdfs:Class ; rdfs:label "Klarner ASP logical model trap space identification method"@en ; rdfs:comment "Optimization-based method rooted in answer set programming (ASP) for computing the trap spaces of a regulatory graph."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000661 . kisao:KISAO_0000337 a rdfs:Class ; rdfs:label "finite element method"@en ; rdfs:comment "A numerical technique for finding approximate solutions of partial differential equations (PDE) as well as of integral equations. The solution approach is based either on eliminating the differential equation completely (steady state problems), or rendering the PDE into an approximating system of ordinary differential equations, which are then numerically integrated using standard techniques such as Euler method [http://identifiers.org/biomodels.kisao/KISAO_0000261], Runge-Kutta [http://identifiers.org/biomodels.kisao/KISAO_0000064], etc."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000369 . kisao:KISAO_0000322 a rdfs:Class ; rdfs:label "hybridity"@en ; rdfs:comment "The basic idea of hybrid simulation methods is to combine the advantages of complementary simulation approaches: the whole system is subdivided into appropriate parts and different simulation methods operate on these parts at the same time."@en ; rdfs:subClassOf kisao:KISAO_0000097 . kisao:KISAO_0000307 a rdfs:Class ; rdfs:label "finite difference method"@en ; rdfs:comment "The finite difference method is based on local approximations of the partial derivatives in a Partial Differential Equation, which are derived by low order Taylor series expansions."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000369 . kisao:KISAO_0000494 a rdfs:Class ; rdfs:label "fully asynchronous updating policy"@en ; rdfs:comment "An updating policy where all enabled transitions occur either independently or (partially) simultaneously. (i.e. considering all possible combinations of enabled transitions). Thus a state has as many successors as the number of combinations of transitions enabled in this state."@en ; rdfs:subClassOf kisao:KISAO_0000492 . kisao:KISAO_0000068 a rdfs:Class ; rdfs:label "deterministic cellular automata update algorithm"@en ; rdfs:comment "A cellular automaton is a discrete model of a regular grid of cells with a finite number of dimensions. Each cell has a finite number of defined states. The automaton changes its state in a discrete manner, meaning that the state of a cell at time t is determined by a function of the states of its neighbours at time t - 1. These neighbours are a selection of cells relative to the specified cell. Famous examples for deterministic cellular automata are Conway's game of life or Wolfram's elementary cellular automata."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000264 . kisao:KISAO_0000106 a rdfs:Class ; rdfs:label "continuous variable"@en ; rdfs:comment "Algorithm, possessing this characteristic, allows the values of a system's variables to change by continuous (non-integral) amounts."@en ; rdfs:subClassOf kisao:KISAO_0000098 . kisao:KISAO_0000689 a rdfs:Class ; rdfs:label "mathematical system"@en ; rdfs:subClassOf kisao:KISAO_0000688 . kisao:KISAO_0000611 a rdfs:Class ; rdfs:label "incremental stochastic simulation algorithm"@en ; rdfs:comment "Performs local averaging over small time-intervals to compute statistics on typical behavior."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000335 . kisao:KISAO_0000481 a rdfs:Class ; rdfs:label "interpolate solution"@en ; rdfs:comment "whether the solver returns an interpolated solution."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000201 . kisao:KISAO_0000651 a rdfs:Class ; rdfs:label "reduced costs"@en ; rdfs:comment "The amount by which an objective function coefficient would have to improve before it would be possible for a corresponding variable to assume a positive value in the optimal solution."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000650 . kisao:KISAO_0000640 a rdfs:Class ; rdfs:label "lower bound"@en ; rdfs:comment "A lower bound on an estimate of a quantity."@en ; rdfs:subClassOf kisao:KISAO_0000641 . kisao:KISAO_0000315 a rdfs:Class ; rdfs:label "lattice gas automata"@en ; rdfs:comment "Lattice gas automata methods are a series of cellular automata methods used to simulate fluid flows. From the LGCA, it is possible to derive the macroscopic Navier-Stokes equations."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000068 . kisao:KISAO_0000211 a rdfs:Class ; rdfs:label "absolute tolerance"@en ; rdfs:comment "This parameter is a positive numeric value specifying the desired absolute tolerance the user wants to achieve."@en ; rdfs:subClassOf kisao:KISAO_0000597 . kisao:KISAO_0000564 a rdfs:Class ; rdfs:label "stochastic Runge-Kutta method"@en ; rdfs:comment "Technique for the approximate numerical solution of a systems of stochastic differential equations (SDEs). The method is a generalisation of the Runge-Kutta method for ordinary differential equations to stochastic differential equations."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000697 . kisao:KISAO_0000534 a rdfs:Class ; rdfs:label "reactions"@en ; rdfs:comment "FVA algorithm [http://www.biomodels.net/kisao/KISAO#KISAO_0000526] parameter: reactions to compute the variablity of."@en ; rdfs:subClassOf kisao:KISAO_0000201 . kisao:KISAO_0000304 a rdfs:Class ; rdfs:label "Radau method"@en ; rdfs:comment "Implicit Runge-Kutta methods based on Radau quadrature."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000064 . kisao:KISAO_0000371 a rdfs:Class ; rdfs:label "stochastic differential equation problem"@en ; rdfs:subClassOf kisao:KISAO_0000405 . kisao:KISAO_0000252 a rdfs:Class ; rdfs:label "partitioning control parameter"@en ; rdfs:subClassOf kisao:KISAO_0000201 . kisao:KISAO_0000589 a rdfs:Class ; rdfs:label "ACB flux sampling method"@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000588 . kisao:KISAO_0000074 a rdfs:Class ; rdfs:label "binomial tau-leaping method"@en ; rdfs:comment "Coarse grained modified version of the next subvolume method [http://identifiers.org/biomodels.kisao/KISAO_0000022] that allows the user to consider both diffusion and reaction events in relatively long simulation time spans as compared with the original method and other commonly used fully stochastic computational methods."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000039 . kisao:KISAO_0000233 a rdfs:Class ; rdfs:label "LSODES"@en ; rdfs:comment "LSODES solves systems dy/dt = f and in the stiff case treats the Jacobian matrix in general sparse form. It determines the sparsity structure on its own, or optionally accepts this information from the user. It then uses parts of the Yale Sparse Matrix Package (YSMP) to solve the linear systems that arise, by a sparse (direct) LU factorization/backsolve method."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000094 . kisao:KISAO_0000051 a rdfs:Class ; rdfs:label "Bortz-Kalos-Lebowitz algorithm"@en ; rdfs:comment "The Bortz-Kalos-Lebowitz (or: kinetic Monte-Carlo-) method is a stochastic method for the simulation of time evolution of processes using (pseudo-)random numbers."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000335 . kisao:KISAO_0000560 a rdfs:Class ; rdfs:label "LSODA/LSODAR hybrid method"@en ; rdfs:comment "Automatically use LSODA or LSODAR as apropriate for the given problem. Use LSODA if the problem has no roots. Use LSODAR if the problem has roots."@en ; rdfs:seeAlso , , , ; rdfs:subClassOf kisao:KISAO_0000094 . kisao:KISAO_0000846 a rdfs:Class ; rdfs:label "product ignoring NaN"@en ; rdfs:comment "The product of a set of values, ignoring Nan entries."@en ; rdfs:subClassOf kisao:KISAO_0000824 . kisao:KISAO_0000278 a rdfs:Class ; rdfs:label "Metropolis Monte Carlo algorithm"@en ; rdfs:comment "A general method, suitable for fast computing machines, for investigating such properties as equations of state for substances consisting of interacting individual molecules is described. The method consists of a modified Monte Carlo integration [http://identifiers.org/biomodels.kisao/KISAO_0000051] over configuration space."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000319 . kisao:KISAO_0000103 a rdfs:Class ; rdfs:label "deterministic system behaviour"@en ; rdfs:comment "Algorithm, possessing this characteristic, simulates the temporal evolution of a system deterministically, so that from a precise initial state the algorithm will always end up in the same final state."@en ; rdfs:subClassOf kisao:KISAO_0000099 . kisao:KISAO_0000856 a rdfs:Class ; rdfs:label "median ignoring NaN"@en ; rdfs:comment "The median of a set of values, ignoring Nan entries."@en ; rdfs:subClassOf kisao:KISAO_0000824 . kisao:KISAO_0000625 a rdfs:Class ; rdfs:label "dense direct solver"@en ; rdfs:subClassOf kisao:KISAO_0000624 . kisao:KISAO_0000827 a rdfs:Class ; rdfs:label "standard error ignoring NaN"@en ; rdfs:comment "The standard error of a set of values, ignoring NaN entries."@en ; rdfs:subClassOf kisao:KISAO_0000824 . kisao:KISAO_0000633 a rdfs:Class ; rdfs:label "computational function"@en ; rdfs:comment "A mathematical function such as the calculation of a minimum, maximum, or mean of a set of values."@en . kisao:KISAO_0000810 a rdfs:Class ; rdfs:label "reduced eigenvalue matrix"@en ; rdfs:comment "The reduced eigenvalue matrix of a model. The dimensions are species by two, where the first column is the real part of the eigenvalues, and the second column is the imaginary part of the eigenvalues."@en ; rdfs:subClassOf kisao:KISAO_0000800 . kisao:KISAO_0000542 a rdfs:Class ; rdfs:label "correction step should use internally generated full Jacobian"@en ; rdfs:comment "Specifies whether the iteration method of the ODE solver’s correction step is chord iteration with an internally generated full Jacobian or functional iteration with no Jacobian. Option is only considered when the user has not supplied a Jacobian function and has not indicated (by setting either upper or lower band) that the Jacobian is banded."@en ; rdfs:subClassOf kisao:KISAO_0000243 . kisao:KISAO_0000673 a rdfs:Class ; rdfs:label "skip reactions that produce negative species amounts"@en ; rdfs:comment "Parameter which instructs a simulation tool to skip reactions that would result in negative amounts of species."@en ; rdfs:subClassOf kisao:KISAO_0000243 . kisao:KISAO_0000084 a rdfs:Class ; rdfs:label "nonnegative Poisson tau-leaping method"@en ; rdfs:comment "The explicit tau-leaping procedure attempts to speed up the stochastic simulation of a chemically reacting system by approximating the number of firings of each reaction channel during a chosen time increment Tau as a Poisson random variable. Since the Poisson random variable can have arbitrarily large sample values, there is always the possibility that this procedure will cause one or more reaction channels to fire so many times during Tau that the population of some reactant species will be driven negative. Two recent papers have shown how that unacceptable occurrence can be avoided by replacing the Poisson random variables with binomial random variables, whose values are naturally bounded. This paper describes a modified Poisson tau-leaping procedure that also avoids negative populations, but is easier to implement than the binomial procedure. The new Poisson procedure also introduces a second control parameter, whose value essentially dials the procedure from the original Poisson tau-leaping at one extreme to the exact stochastic simulation algorithm at the other; therefore, the modified Poisson procedure will generally be more accurate than the original Poisson procedure [http://identifiers.org/biomodels.kisao/KISAO_0000040]."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000039 . kisao:KISAO_0000531 a rdfs:Class ; rdfs:label "fraction of optimum"@en ; rdfs:comment "Fraction of the optimum solution which must be maintained."@en ; rdfs:subClassOf kisao:KISAO_0000201 . kisao:KISAO_0000644 a rdfs:Class ; rdfs:label "maximum flux"@en ; rdfs:comment "Maximum possible flux such as computed by flux variability analysis (FVA, KISAO_0000526)."@en ; rdfs:subClassOf kisao:KISAO_0000639 . kisao:KISAO_0000614 a rdfs:Class ; rdfs:label "implementation"@en ; rdfs:comment "An implementation of an algorithm. For example, simulation tools can this parameter to differentiate among C, Python, and Java implementations of the same algorithms and allow investigators to select one of these specific implementations through SED-ML."@en ; rdfs:subClassOf kisao:KISAO_0000243 . kisao:KISAO_0000382 a rdfs:Class ; rdfs:label "modified midpoint method"@en ; rdfs:comment """The modified midpoint method is globally a second order method for approximating the solution of the initial value problem y' = f(x, y), y(x0) = y0, which advances a vector of dependent variables y(x) from a point x to a point x + H by a sequence of n substeps each of size h, h = H/n. """@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000064 . kisao:KISAO_0000311 a rdfs:Class ; rdfs:label "type of domain geometry handling"@en ; rdfs:subClassOf kisao:KISAO_0000097 . kisao:KISAO_0000097 a rdfs:Class ; rdfs:label "modelling and simulation algorithm characteristic"@en ; rdfs:comment "Simulation algorithm property, which can, for example, describe the model, such as the type of variables (discrete or continuous), and information on the treatment of spatial descriptions, or can be a numerical characteristic, such as the system's behaviour (deterministic or stochastic) as well as the progression mechanism (fixed or adaptive time steps)."@en . kisao:KISAO_0000590 a rdfs:Class ; rdfs:label "ACHR flux sampling method"@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000588 . kisao:KISAO_0000340 a rdfs:Class ; rdfs:label "h-p version of the finite element method"@en ; rdfs:comment "In h-p version of 'finite difference method' [http://identifiers.org/biomodels.kisao/KISAO_0000337] the two approaches of mesh refinement and degree enchacement are combined."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000337 . kisao:KISAO_0000684 a rdfs:Class ; rdfs:label "number of steps per output"@en ; rdfs:comment "Number of simulation steps between each simulation output."@en ; rdfs:subClassOf kisao:KISAO_0000244 . kisao:KISAO_0000282 a rdfs:Class ; rdfs:label "KINSOL"@en ; rdfs:comment "KINSOL solves algebraic systems in real N-space, written as F(u)=0, F:RN->RN, given an initial guess u0. The basic method is either a modified or an inexact Newton iteration [http://identifiers.org/biomodels.kisao/KISAO_0000408]. The linear systems that arise are solved with either a direct (dense or banded) solver (serial version only), or one of the Krylov iterative solvers [http://identifiers.org/biomodels.kisao/KISAO_0000354]. In the Krylov case, the user can (optionally) supply a right preconditioner."@en ; rdfs:seeAlso , , ; rdfs:subClassOf kisao:KISAO_0000408 . kisao:KISAO_0000256 a rdfs:Class ; rdfs:label "virtual box side length"@en ; rdfs:comment "The 'virtual box side length' is a parameter of 'Brownian diffusion Smoluchowski method' [http://identifiers.org/biomodels.kisao/KISAO_0000057]. It requests the length of one side of a box."@en ; rdfs:subClassOf kisao:KISAO_0000260 . kisao:KISAO_0000090 a rdfs:Class ; rdfs:label "LSODI"@en ; rdfs:comment "LSODI solves systems given in linearly implicit form, including differential-algebraic systems."@en ; rdfs:seeAlso , ; rdfs:subClassOf kisao:KISAO_0000094 . kisao:KISAO_0000345 a rdfs:Class ; rdfs:label "h-p cloud method"@en ; rdfs:comment "A meshless method, which uses a partition of unity to construct the family of h-p cloud functions. "@en ; rdfs:subClassOf kisao:KISAO_0000369 . kisao:KISAO_0000318 a rdfs:Class ; rdfs:label "Gauss-Legendre Runge-Kutta method"@en ; rdfs:comment "So called 'Open Formula', two points formula, three points formula, four points formula, five points formula and six points formula of the Runge-Kutta method to solve the initial value problem of the ordinary differential equation. These formulas use the points and weights from the Gauss-Legendre Quadrature formulas for finding the value of the definite integral."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000064 . kisao:KISAO_0000816 a rdfs:Class ; rdfs:label "link matrix"@en ; rdfs:comment "The link matrix of a model."@en ; rdfs:subClassOf kisao:KISAO_0000800 . kisao:KISAO_0000419 a rdfs:Class ; rdfs:label "metamodelling method"@en ; rdfs:comment "Deterministic dynamic models of complex biological systems contain a large number of parameters and state variables, related through nonlinear differential equations with various types of feedback. A metamodel of such a dynamic model is a statistical approximation model that maps variation in parameters and initial conditions (inputs) to variation in features of the trajectories of the state variables (outputs) throughout the entire biologically relevant input space."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000000 . kisao:KISAO_0000430 a rdfs:Class ; rdfs:label "variables preprocessing parameter"@en ; rdfs:subClassOf kisao:KISAO_0000201 . kisao:KISAO_0000334 a rdfs:Class ; rdfs:label "multiparticle lattice gas automata"@en ; rdfs:comment "An algorithm which allows for an arbitrary number of particles, while keeping the benefits of the cellular automata approach [http://identifiers.org/biomodels.kisao/KISAO_0000315]."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000068 . kisao:KISAO_0000578 a rdfs:Class ; rdfs:label "nested algorithm"@en ; rdfs:comment "A nested algorithm of an algorithm"@en ; rdfs:subClassOf kisao:KISAO_0000243 . kisao:KISAO_0000546 a rdfs:Class ; rdfs:label "convex optimization algorithm"@en ; rdfs:comment "Optimization of a convex function over a convex set. Convex optimization is subclass of global optimization because conveness gaurantees that each local optimum is a global optimum."@en ; rdfs:subClassOf kisao:KISAO_0000472 . kisao:KISAO_0000237 a rdfs:Class ; rdfs:label "approximate solution"@en ; rdfs:comment "Approximation algorithms are algorithms used to find approximate solutions to optimization problems. Approximation algorithms are often associated with NP-hard problems; since it is unlikely that there can ever be efficient polynomial time exact algorithms solving NP-hard problems, one settles for polynomial time sub-optimal solutions. Unlike heuristics, which usually only find reasonably good solutions reasonably fast, one wants provable solution quality and provable run time bounds. Ideally, the approximation is optimal up to a small constant factor (for instance within 5% of the optimal solution). Approximation algorithms are increasingly being used for problems where exact polynomial-time algorithms are known but are too expensive due to the input size."@en ; rdfs:subClassOf kisao:KISAO_0000235 . kisao:KISAO_0000022 a rdfs:Class ; rdfs:label "Elf and Ehrenberg method"@en ; rdfs:comment "Sub-volume stochastic reaction-diffusion method that is a combination of the Direct Method [http://identifiers.org/biomodels.kisao/KISAO_0000029] for sampling the time for a next reaction or diffusion event in each subvolume, with Gibson and Bruck's Next Reaction Method [http://identifiers.org/biomodels.kisao/KISAO_0000027], which is used to keep track of in which subvolume an event occurs next. The subvolumes are kept sorted in a queue, implemented as a binary tree, according to increasing time of the next event. When an event has occurred in the subvolume at the top of the queue, new event times need to be sampled only for one (the event is a chemical reaction) or two (the event is a diffusion jump) subvolume(s)."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000095 . kisao:KISAO_0000362 a rdfs:Class ; rdfs:label "implicit-state Doob-Gillespie algorithm"@en ; rdfs:comment """The algorithm uses a representation of the system together with a super-approximation of its ‘event horizon’ (all events that may happen next), and a specific correction scheme to obtain exact timings. Being completely local and not based on any kind of enumeration, this algorithm has a per event time cost which is independent of (i) the size of the set of generable species (which can even be infinite), and (ii) independent of the size of the system (ie, the number of agent instances). The algorithm can be refined, using concepts derived from the classical notion of causality, so that in addition to the above one also has that the even cost is depending (iii) only logarithmically on the size of the model (ie, the number of rules). """@en ; rdfs:subClassOf kisao:KISAO_0000017 . kisao:KISAO_0000332 a rdfs:Class ; rdfs:label "ER-leap initial leap"@en ; rdfs:comment "L (initial step) is a parameter of 'exact R-leaping method' [http://identifiers.org/biomodels.kisao/KISAO_0000331]. ''We will assume that the reaction event to be bounded occurs within a run of L events in the SSA algorithm[http://identifiers.org/biomodels.kisao/KISAO_0000029], in order to execute L reactions at once in the manner of the R-leap algorithm[http://identifiers.org/biomodels.kisao/KISAO_0000230]''."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000244 . kisao:KISAO_0000655 a rdfs:Class ; rdfs:label "rate"@en ; rdfs:comment "Speed at which a process is occuring such as the temporal rate of a chemical reaction,"@en ; rdfs:subClassOf kisao:KISAO_0000820 . kisao:KISAO_0000398 a rdfs:Class ; rdfs:label "iterative method for solving a system of linear equations"@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000624 . kisao:KISAO_0000095 a rdfs:Class ; rdfs:label "sub-volume stochastic reaction-diffusion algorithm"@en ; rdfs:comment "Stochastic method using a combination of discretisation of compartment volumes into voxels and Gillespie-like algorithm [http://identifiers.org/biomodels.kisao/KISAO_0000241] to simulate the evolution of the system."@en ; rdfs:subClassOf kisao:KISAO_0000335 . kisao:KISAO_0000677 a rdfs:Class ; rdfs:label "maximum number of steps for presimulation"@en ; rdfs:comment "Maximum number of steps to take in presimulating a model prior to analysis."@en ; rdfs:subClassOf kisao:KISAO_0000415 . kisao:KISAO_0000408 a rdfs:Class ; rdfs:label "Newton-type method"@en ; rdfs:comment """A method which attacks the solution of a nonlinear problem F(x) = 0 by solving a sequence of liner problems of the same kind. The solution of the system F(x)=0 can be interpreted as a steady state of a dynamic system x'(t)=F(x(t)). The Newton approach will only work if the fixed point [http://identifiers.org/biomodels.teddy/TEDDY_0000086] of the dinamic system is attractive [http://identifiers.org/biomodels.teddy/TEDDY_0000094]."""@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000631 . kisao:KISAO_0000615 a rdfs:Class ; rdfs:label "fully-implicit regular grid finite volume method with a variable time step"@en ; rdfs:subClassOf kisao:KISAO_0000285 . kisao:KISAO_0000477 a rdfs:Class ; rdfs:label "linear solver"@en ; rdfs:comment "the linear solver used by the solver during a Newton iteration"@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000201 . kisao:KISAO_0000837 a rdfs:Class ; rdfs:label "particle number"@en ; rdfs:comment "The extensive quantity particle number, or, the molar amount of the entity multiplied by Avogadro's number."@en ; rdfs:subClassOf kisao:KISAO_0000831 . kisao:KISAO_0000274 a rdfs:Class ; rdfs:label "first-passage Monte Carlo algorithm"@en ; rdfs:comment "We present a novel Monte Carlo algorithm for N diffusing finite particles that react on collisions. Using the theory of first-passage processes and time dependent Green's functions, we break the difficult N-body problem into independent single- and two-body propagations circumventing numerous diffusion hops used in standard Monte Carlo simulations. The new algorithm is exact, extremely efficient, and applicable to many important physical situations in arbitrary integer dimensions."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000319 . kisao:KISAO_0000581 a rdfs:Class ; rdfs:label "BKMC"@en ; rdfs:comment "The Boolean kinetic Monte Carlo method (BKMC) is a natural generalization of the asynchronous Boolean simulation method, with a direct probabilistic interpretation. In the BKMC framework, the dynamics is parameterized by a biological time and the order of update is noisy, which is less strict than priority classes introduced in GINsin. A BKMC model is specified by logical rules as in regular Boolean models but with a more precise information: a numerical rate is added for each transition of each node."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000319 , kisao:KISAO_0000573 . kisao:KISAO_0000696 a rdfs:Class ; rdfs:label "steady state root-finding problem"@en ; rdfs:subClassOf kisao:KISAO_0000370 . kisao:KISAO_0000637 a rdfs:Class ; rdfs:label "derived property"@en ; rdfs:comment "An output of a simulation which can be derived from its primary outputs."@en ; rdfs:subClassOf kisao:KISAO_0000820 . kisao:KISAO_0000592 a rdfs:Class ; rdfs:label "dynamic rFBA"@en ; rdfs:comment "Method for predicting the dynamics of metabolic fluxes under patterns of the regulation of gene expression"@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000595 . kisao:KISAO_0000699 a rdfs:Class ; rdfs:label "DAE Solver"@en ; rdfs:comment "A DAE solver is the general category of packages such as IDA-like methods [http://identifiers.org/biomodels.kisao/KISAO_0000432] that solve systems of differential algebraic equations (DAEs). DAEs are a superset of ODEs that may additionally contain algebraic equations or 'fast' reactions."@en ; rdfs:subClassOf kisao:KISAO_0000000 . kisao:KISAO_0000822 a rdfs:Class ; rdfs:label "extensive property"@en ; rdfs:comment "An extensive variable such as an amount, particle number, or mass."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000820 . kisao:KISAO_0000648 a rdfs:Class ; rdfs:label "step"@en ; rdfs:comment "Iteration such as along a pseudo timecourse of a logical simulation."@en ; rdfs:subClassOf kisao:KISAO_0000831 . kisao:KISAO_0000354 a rdfs:Class ; rdfs:label "Krylov subspace projection method"@en ; rdfs:comment "Krylov subspace method is an iterative linear equation method, which builds up Krylov subspaces and look for good approximations to eigenvectors and invariant subspaces within the Krylov spaces."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000398 . kisao:KISAO_0000688 a rdfs:Class ; rdfs:label "type of system described"@en ; rdfs:subClassOf kisao:KISAO_0000097 . kisao:KISAO_0000455 a rdfs:Class ; rdfs:label "prioritized updating policy"@en ; rdfs:comment "An updating policy that chooses a transition in a prioritized way."@en ; rdfs:subClassOf kisao:KISAO_0000453 . kisao:KISAO_0000434 a rdfs:Class ; rdfs:label "Higham-Hall method"@en ; rdfs:comment "The equilibrium theory of Hall and Higham (1988) can be used to determine whether a Runge-Kutta algorithm will perform smoothly when stability restricts the stepsize. Higham-Hall method is a fifth order embedded Runge-Kutta method [http://identifiers.org/biomodels.kisao/KISAO_0000302], which behaves smoothly with respect to the standard type of stepsize controllers."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000435 . kisao:KISAO_0000815 a rdfs:Class ; rdfs:label "flux control coefficient matrix (scaled)"@en ; rdfs:comment "The scaled flux control coefficient matrix. The dimensions are reactions by reactions."@en ; rdfs:subClassOf kisao:KISAO_0000800 . kisao:KISAO_0000379 a rdfs:Class ; rdfs:label "Bulirsch-Stoer algorithm"@en ; rdfs:comment "The Bulirsch-Stoer method is an adaptive method which uses Gragg's modified midpoint method [http://identifiers.org/biomodels.kisao/KISAO_0000382] to estimate the solution of an initial value problem for various step sizes. The estimates are fit to a \"diagonal\" rational function or a polynomial as a function of the step size and the limit as the step size tends to zero is taken as the final estimate."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000380 . kisao:KISAO_0000015 a rdfs:Class ; rdfs:label "Gillespie first reaction algorithm"@en ; rdfs:comment "Stochastic simulation algorithm using the reaction probability density function (next-reaction density function), giving the probability that the next reaction will happen in a given time interval. To choose the next reaction to fire, the algorithm calculates a tentative reaction time for each reaction and then select the smallest."@en ; rdfs:seeAlso , ; rdfs:subClassOf kisao:KISAO_0000241 . kisao:KISAO_0000501 a rdfs:Class ; rdfs:label "DOA-DFBA"@en ; rdfs:comment "Dynamic Flux Balance Analysis (DFBA) [http://identifiers.org/biomodels.kisao/KISAO_0000499] couples flux balance analysis (FBA) [http://identifiers.org/biomodels.kisao/KISAO_0000437] model approaches with dynamic model approaches. The dynamic optimization approach (DOA) discretizes the time horizon and optimizes simultaneously over the entire time period of interest by solving a nonlinear programming problem (NLP)."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000499 . kisao:KISAO_0000535 a rdfs:Class ; rdfs:label "VODE"@en ; rdfs:comment "VODE provides implicit Adams method (for non-stiff problems) and a method based on backward differentiation formulas (BDF) (for stiff problems)."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000433 . kisao:KISAO_0000281 a rdfs:Class ; rdfs:label "multistep method"@en ; rdfs:comment "A numerical method for differential equations which is based on several values of the solution."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000000 . kisao:KISAO_0000349 a rdfs:Class ; rdfs:label "method of finite spheres"@en ; rdfs:comment "Method of finite spheres is truly meshless in the sense that the nodes are placed and the numerical integration is performed without a mesh. Some of the novel features of the method of finite spheres are the numerical integration scheme and the way in which the Dirichlet boundary conditions are incorporated."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000369 . kisao:KISAO_0000338 a rdfs:Class ; rdfs:label "h-version of the finite element method"@en ; rdfs:comment "Classical form of the 'finite element method' [http://identifiers.org/biomodels.kisao/KISAO_0000337], in which polynomials of fixed degree p are used and the mesh is refined to increase accuracy. Can be considered as a special case of the h-p version [http://identifiers.org/biomodels.kisao/KISAO_0000340]."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000337 . kisao:KISAO_0000574 a rdfs:Class ; rdfs:label "species transition probabilities"@en ; rdfs:comment "Probability of each species to be chosen for the next state transition."@en ; rdfs:subClassOf kisao:KISAO_0000201 . kisao:KISAO_0000853 a rdfs:Class ; rdfs:label "count"@en ; rdfs:comment "The number of non-zero elements of a set of values. If the values contain NaN the count is NaN."@en ; rdfs:subClassOf kisao:KISAO_0000824 . kisao:KISAO_0000626 a rdfs:Class ; rdfs:label "band direct solver"@en ; rdfs:subClassOf kisao:KISAO_0000624 . kisao:KISAO_0000512 a rdfs:Class ; rdfs:label "praxis"@en ; rdfs:comment "Praxis is a direct search method that searches for the minimum of a nonlinear function without requiring (or attempting to calculate) derivatives of that function. Praxis was developed by Brent after the method proposed by Powell. The inspiration for Praxis was the well-known method of minimising each adjustable parameter (direction) at a time - the principal axes method. In Praxis directions are chosen that do not coincide with the principal axes, in fact if the objective function is quadratic then these will be conjugate directions, assuring a fast convergence rate."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000471 . kisao:KISAO_0000288 a rdfs:Class ; rdfs:label "backward differentiation formula"@en ; rdfs:comment "The backward differentiation formulas (BDF) are implicit multistep methods based on the numerical differentiation of a given function and are wildly used for integration of stiff differential equations."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000281 . kisao:KISAO_0000076 a rdfs:Class ; rdfs:label "Stundzia and Lumsden method"@en ; rdfs:comment "Sub-volume stochastic reaction-diffusion method that using Green's function to link the bulk diffusion coefficient D in Fick's differential law to the corresponding transition rate probability for diffusion of a particle between finite volume elements. This generalized stochastic algorithm enables to numerically calculate the time evolution of a spatially inhomogeneous mixture of reaction-diffusion species in a finite volume. The time step is stochastic and is generated by a probability distribution determined by the intrinsic reaction kinetics and diffusion dynamics."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000095 . kisao:KISAO_0000343 a rdfs:Class ; rdfs:label "generalized finite element method"@en ; rdfs:comment "The GFEM is a generalization of the classical 'finite element method' [http://identifiers.org/biomodels.kisao/KISAO_0000337] — in its h [http://identifiers.org/biomodels.kisao/KISAO_0000338], p [http://identifiers.org/biomodels.kisao/KISAO_0000339], and h-p versions [http://identifiers.org/biomodels.kisao/KISAO_0000340]— as well as of the various forms of meshless methods used in engineering."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000369 . kisao:KISAO_0000523 a rdfs:Class ; rdfs:label "cooling factor"@en ; rdfs:comment "Rate by which the temperature is reduced from one cycle to the next, given by the formula: Tnew=Told*\"Cooling Factor\". The simulated annealing algorithm works best if the temperature is reduced at a slow rate, so this value should be close to 1."@en ; rdfs:subClassOf kisao:KISAO_0000521 . kisao:KISAO_0000289 a rdfs:Class ; rdfs:label "Adams method"@en ; rdfs:comment "Adams' methods are multi-step methods used for the numerical integration of initial value problems in Ordinary Differential Equations (ODE's). Adams' algorithm consists of two parts: firstly, a starting procedure which provides y1, ... , yk-1 ( approximations to the exact solution at the points x0 + h, ... , x0 + (k - 1)h ) and, secondly, a multistep formula to obtain an approximation to the exact solution y(x0 + kh). This is then applied recursively, based on the numerical approximation of k successive steps, to compute y(x0 + (k + 1)h)."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000281 . kisao:KISAO_0000557 a rdfs:Class ; rdfs:label "absolute steady-state tolerance"@en ; rdfs:comment "Absolute error tolerance of the steady-state."@en ; rdfs:subClassOf kisao:KISAO_0000211 . kisao:KISAO_0000666 a rdfs:Class ; rdfs:label "Jacobian epsilon"@en ; rdfs:subClassOf kisao:KISAO_0000242 . kisao:KISAO_0000033 a rdfs:Class ; rdfs:label "Rosenbrock method"@en ; rdfs:comment "Some general implicit processes are given for the solution of simultaneous first-order differential equations. These processes, which use successive substitution, are implicit analogues of the (explicit) Runge-Kutta processes. They require the solution in each time step of one or more set of simultaneous linear equations, usually of a special and simple form. Processes of any required order can be devised, and they can be made to have a wide margin of stability when applied to a linear problem."@en ; rdfs:seeAlso , ; rdfs:subClassOf kisao:KISAO_0000064 . kisao:KISAO_0000826 a rdfs:Class ; rdfs:label "standard deviation ignoring NaN"@en ; rdfs:comment "The standard deviation of a set of values, ignoring NaN entries."@en ; rdfs:subClassOf kisao:KISAO_0000824 . kisao:KISAO_0000102 a rdfs:Class ; rdfs:label "spatial description"@en ; rdfs:comment "Algorithm, possessing this characteristic, takes into account the location of the reacting components."@en ; rdfs:subClassOf kisao:KISAO_0000097 . kisao:KISAO_0000479 a rdfs:Class ; rdfs:label "upper half-bandwidth"@en ; rdfs:comment "the upper half-bandwidth value used by the Banded linear solver or preconditioner (a value between 0 and n-1 with n the number of ODEs/DAEs in the model)."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000482 . kisao:KISAO_0000520 a rdfs:Class ; rdfs:label "evolutionary algorithm"@en ; rdfs:comment "An optimisation algorithm that mimics evolution and is based on reproduction and selection."@en ; rdfs:subClassOf kisao:KISAO_0000472 . kisao:KISAO_0000423 a rdfs:Class ; rdfs:label "partial least squares regression-like method"@en ; rdfs:comment "Method for building regression models between independent and dependent variables."@en ; rdfs:subClassOf kisao:KISAO_0000419 . kisao:KISAO_0000310 a rdfs:Class ; rdfs:label "method of lines"@en ; rdfs:comment "The method of lines is a general technique for solving partial differential equations (PDEs) by typically using finite difference relationships for the spatial derivatives and ordinary differential equations for the time derivative."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000369 . kisao:KISAO_0000807 a rdfs:Class ; rdfs:label "elasticity coefficient (scaled)"@en ; rdfs:comment "A scaled elasticity coefficient of any reaction with respect to an independent element (such as a global parameter or boundary species)."@en ; rdfs:subClassOf kisao:KISAO_0000800 . kisao:KISAO_0000376 a rdfs:Class ; rdfs:label "linearity of equation"@en ; rdfs:comment "Linear differential equations are of the form Ly = f, where the differential operator L is a linear operator, y is the unknown function, and the right hand side f is a given function of the same nature as y."@en ; rdfs:subClassOf kisao:KISAO_0000370 . kisao:KISAO_0000263 a rdfs:Class ; rdfs:label "NFSim agent-based simulation method"@en ; rdfs:comment "A generalization a rule-based version of 'Gillespie's direct method' (SSA) [http://identifiers.org/biomodels.kisao/KISAO_0000029]. The method is guaranteed to produce the same results as the exact SSA [http://identifiers.org/biomodels.kisao/KISAO_0000029] by cycling over three primary steps. First, NFsim calculates the probability or propensity for each rule to take effect given the current molecular states. Second, it samples the time to the next reaction event and selects the corresponding reaction rule. Finally, NFsim executes the selected reaction by applying the rule and updating the molecular agents accordingly."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000017 . kisao:KISAO_0000411 a rdfs:Class ; rdfs:label "Newton-like method"@en ; rdfs:comment "A 'Newton-type method' [http://identifiers.org/biomodels.kisao/KISAO_0000408] which is characterized by the fact that, in finite dimension, the Jacodian matrices are either replaced by some fixed 'close by' Jacobian F'(z) with z not equal to the initial guess x[0], or by some approximation so that: M'(x[0])deltax[k]=-F(x[k]), x[k+1]=x[k]+deltax[k], k=0,1,..."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000408 . kisao:KISAO_0000351 a rdfs:Class ; rdfs:label "multinomial tau-leaping method"@en ; rdfs:comment "The multinomial tau-leaping method is an extension of the binomial tau-leaping method [http://identifiers.org/biomodels.kisao/KISAO_0000074] to networks with arbitrary multiple-channel reactant dependencies. Improvements were achieved by a combination of three factors: First, tau-leaping steps are determined simply and efficiently using a-priori information and Poisson distribution based estimates of expectation values for reaction numbers. Second, networks are partitioned into closed groups of reactions and corresponding reactants in which no group reactant set is found in any other group. Third, product formation is factored into upper bound estimation of the number of times a particular reaction occurs."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000039 . kisao:KISAO_0000568 a rdfs:Class ; rdfs:label "NLEQ1"@en ; rdfs:comment """Damped Newton-algorithm with rank strategy for systems of highly nonlinear equations. Global Newton method with error oriented convergence criterion; arbitrary selection of direct linear equation solver."""@en ; rdfs:seeAlso , ; rdfs:subClassOf kisao:KISAO_0000408 . kisao:KISAO_0000086 a rdfs:Class ; rdfs:label "Fehlberg method"@en ; rdfs:comment "The method was developed by the German mathematician Erwin Fehlberg and is based on the class of Runge-Kutta methods. The Runge-Kutta-Fehlberg method uses an O(h4) method together with an O(h5) method that uses all of the points of the O(h4) method, and hence is often referred to as an RKF45 method. Similar schemes with different orders have since been developed. By performing one extra calculation that would be required for an RK5 method, the error in the solution can be estimated and controlled and an appropriate step size can be determined automatically, making this method efficient for ordinary problems of automated numerical integration of ordinary differential equations."@en ; rdfs:seeAlso , ; rdfs:subClassOf kisao:KISAO_0000435 . kisao:KISAO_0000858 a rdfs:Class ; rdfs:label "variance ignoring NaN"@en ; rdfs:comment "The variance of a set of values, ignoring Nan entries."@en ; rdfs:subClassOf kisao:KISAO_0000824 . kisao:KISAO_0000670 a rdfs:Class ; rdfs:label "use multiple steps"@en ; rdfs:comment "Whether to perform a multiple time step simulation."@en ; rdfs:subClassOf kisao:KISAO_0000243 . kisao:KISAO_0000547 a rdfs:Class ; rdfs:label "linear programming"@en ; rdfs:comment "Method to achieve the best outcome (such as maximum profit or lowest cost) in a mathematical model whose requirements are represented by linear relationships."@en ; rdfs:subClassOf kisao:KISAO_0000546 . kisao:KISAO_0000412 a rdfs:Class ; rdfs:label "inexact Newton method"@en ; rdfs:comment """For extremely large scale nonlinear problems the arising linear systems for the Newton corrections can no longer be solved directly ('exactly'), but must be solved iterativly ('inexactly) - which gives the name inexact Newton methods. The whole scheme then consists of an inner iteration (at Newton step k): F'(x[k])deltaxi[k]=-F(x[k])+ri[k], k=0,1,... xi[k+1]=x[k]+deltaxi[k], i=0,1,..,imax[k] in terms of residuals ri[k] and an outer iteration where, given x[0], the iterates are defined as x[k+1]=xi[k+1] for i=imax[k], k=0,1,..."""@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000408 . kisao:KISAO_0000570 a rdfs:Class ; rdfs:label "auto reduce tolerances"@en ; rdfs:comment "Whether to automatically reduce tolerances."@en ; rdfs:subClassOf kisao:KISAO_0000242 , kisao:KISAO_0000243 . kisao:KISAO_0000536 a rdfs:Class ; rdfs:label "ZVODE"@en ; rdfs:comment "ZVODE provides implicit Adams method (for non-stiff problems) and a method based on backward differentiation formulas (BDF) (for stiff problems)."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000433 . kisao:KISAO_0000506 a rdfs:Class ; rdfs:label "genetic algorithm"@en ; rdfs:comment "The genetic algorithm (GA) is a computational technique that mimics evolution and is based on reproduction and selection. A GA is composed of individuals that reproduce and compete, each one is a potential solution to the (optimization) problem and is represented by a \"genome\" where each gene corresponds to one adjustable parameter. At each generation of the GA, each individual is paired with one other at random for reproduction. Two offspring are produced by combining their genomes and allowing for \"cross-over\", i.e., the two new individuals have genomes that are formed from a combination of the genomes of their parents. Also each new gene might have mutated, i.e. the parameter value might have changed slightly. At the end of the generation, the algorithm has double the number of individuals. Then each of the individuals is confronted with a number of others to count how many does it outperform (the number of wins is the number of these competitors that represent worse solutions than itself). All the individuals are ranked by their number of wins, and the population is again reduced to the original number of individuals by eliminating those which have worse fitness (solutions)."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000520 . kisao:KISAO_0000508 a rdfs:Class ; rdfs:label "evolutionary programming"@en ; rdfs:comment "Evolutionary programming (EP) is a computational technique that mimics evolution and is based on reproduction and selection. An EP algorithm is composed of individuals that reproduce and compete, each one is a potential solution to the (optimization) problem and is represented by a \"genome\" where each gene corresponds to one adjustable parameter. At each generation of the EP, each individual reproduces asexually, i.e. divides into two individuals. One of these contains exactly the same \"genome\" as the parent while the other suffers some mutations (the parameter values of each gene change slightly). At the end of the generation, the algorithm has double the number of individuals. Then each of the individuals is confronted with a number of others to count how many does it outperform (the number of wins is the number of these competitors that represent worse solutions than itself). All the individuals are ranked by their number of wins, and the population is again reduced to the original number of individuals by eliminating those which have worse fitness (solutions)."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000520 . kisao:KISAO_0000220 a rdfs:Class ; rdfs:label "maximum BDF order"@en ; rdfs:comment "This parameter is a positive integer value specifying the maximal order the stiff BDF integration method [http://identifiers.org/biomodels.kisao/KISAO_0000288] shall attempt before switching to smaller internal step sizes."@en ; rdfs:subClassOf kisao:KISAO_0000484 . kisao:KISAO_0000586 a rdfs:Class ; rdfs:label "Gibson-Bruck next reaction algorithm with indexed priority queue"@en ; rdfs:subClassOf kisao:KISAO_0000027 . kisao:KISAO_0000847 a rdfs:Class ; rdfs:label "product"@en ; rdfs:comment "The product of a set of values. If the values contain NaN the product is NaN."@en ; rdfs:subClassOf kisao:KISAO_0000824 . kisao:KISAO_0000253 a rdfs:Class ; rdfs:label "coarse-graining factor"@en ; rdfs:comment "The time in each Monte-Carlo iteration of 'binomial tau-leaping method' [http://identifiers.org/biomodels.kisao/KISAO_0000074] is updated with the time increments tau=f/(a1+a2+...+aM). Here 1/(a1+a2+...+aM) is the averaged microscopic increment of the SSA [http://identifiers.org/biomodels.kisao/KISAO_0000029] and f is a coarse-graining factor, controlling the speed-up."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000244 . kisao:KISAO_0000842 a rdfs:Class ; rdfs:label "standard deviation"@en ; rdfs:comment "The standard deviation of a set of values. If the values contain NaN the standard deviation is NaN."@en ; rdfs:subClassOf kisao:KISAO_0000824 . kisao:KISAO_0000075 a rdfs:Class ; rdfs:label "Gillespie multi-particle method"@en ; rdfs:comment "Combination of the multiparticle method for diffusion [http://identifiers.org/biomodels.kisao/KISAO_0000334] and the SSA [http://identifiers.org/biomodels.kisao/KISAO_0000029]."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000335 . kisao:KISAO_0000575 a rdfs:Class ; rdfs:label "hybrid tau-leaping method"@en ; rdfs:comment "A continuously coupled hybrid deterministic/stochastic simulation algorithm for biochemical networks. Biochemical species are classified as continuous, discrete, or switch. Tau-leaping is used to simulate stochastic species, and LSODA or another ODE integration method is used to simulate continuous species. Switch species are dynamically classified as either continuous or discrete at each timestep depending on a user defined error tolerance."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000039 , kisao:KISAO_0000352 . kisao:KISAO_0000248 a rdfs:Class ; rdfs:label "tau-leaping delta"@en ; rdfs:comment "Tau-leaping delta specifies how close two symmetric transition rates must be before we classify them as in partial-equilibrium. Only applies to the implicit tau routine [http://identifiers.org/biomodels.kisao/KISAO_0000045]."@en ; rdfs:subClassOf kisao:KISAO_0000252 . kisao:KISAO_0000435 a rdfs:Class ; rdfs:label "embedded Runge-Kutta 5(4) method"@en ; rdfs:comment "An embedded Runge-Kutta integrator of order 5(4)."@en ; rdfs:subClassOf kisao:KISAO_0000302 . kisao:KISAO_0000264 a rdfs:Class ; rdfs:label "cellular automata update method"@en ; rdfs:comment "Cellular automata are mathematical idealizations of physical systems in which space and time are discrete, and physical quantities take on a finite set of discrete values. A cellular automaton consists of a regular uniform lattice (or ''array''), usually infinite in extent, with a discrete variable at each site (''cell''). A cellular automaton evolves in discrete time steps, with the value of the variable at one site being affected by the values of variables at sites in its ''neighbourhood'' on the previous time step. The neighbourhood of a site is typically taken to be the site itself and all immediately adjacent sites. The variables at each site are updated simultaneously (''synchronously''), based on the values of the variables in their neighbourhood at the preceding time step, and according to a definite set of ''local rules''."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000363 . kisao:KISAO_0000634 a rdfs:Class ; rdfs:label "scaled property"@en ; rdfs:subClassOf kisao:KISAO_0000820 . kisao:KISAO_0000495 a rdfs:Class ; rdfs:label "random asynchronous updating policy"@en ; rdfs:comment "An updating policy where a single transition is picked randomly from the set of transitions enabled in this state. Thus a state will have at most one successor."@en ; rdfs:subClassOf kisao:KISAO_0000452 , kisao:KISAO_0000492 . kisao:KISAO_0000674 a rdfs:Class ; rdfs:label "presimulate"@en ; rdfs:comment "Whether a model should be presimulated prior to analysis."@en ; rdfs:subClassOf kisao:KISAO_0000243 . kisao:KISAO_0000372 a rdfs:Class ; rdfs:label "partial differential equation problem"@en ; rdfs:subClassOf kisao:KISAO_0000405 . kisao:KISAO_0000243 a rdfs:Class ; rdfs:label "method switching control parameter"@en ; rdfs:comment "Parameters describing threshold conditions for algorithms that switch between different methods."@en ; rdfs:subClassOf kisao:KISAO_0000201 . kisao:KISAO_0000386 a rdfs:Class ; rdfs:label "scaled preconditioned generalized minimal residual method"@en ; rdfs:comment "A scaled preconditioned version of 'generalized minimal residual algorithm' [http://identifiers.org/biomodels.kisao/KISAO_0000353]. For linear system Ax = b a preconditioner matrix P that approximates A is sought, for which linear system Px = b can be solved easily. Preconditioning is applied on the left only. Scaling is done using diagonal matrix D whose diagonal elements are weights w^i = rtol|y^i| +atol^i, where rtol is 'relative tolerance' [http://identifiers.org/biomodels.kisao/KISAO_0000209] and atol is 'absolute tolerance' [http://identifiers.org/biomodels.kisao/KISAO_0000211]."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000353 . kisao:KISAO_0000600 a rdfs:Class ; rdfs:label "hybrid adaptive Gibson - Milstein method"@en ; rdfs:comment "A hybrid stochastic method partitions the system into subsets of fast and slow reactions and approximates the fast reactions as a continuous Markov process, using a chemical Langevin equation, and accurately describes the slow dynamics using the Gibson algorithm. Fixed time step Milstein is used for approximate numerical solution of CLE."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000352 . kisao:KISAO_0000299 a rdfs:Class ; rdfs:label "Butcher-Kuntzmann method"@en ; rdfs:comment "From a theoretical point of view, the Butcher-Kuntzmann Runge-Kutta methods belong to the best step-by-step methods for nonstiff problems. These methods integrate first-order initial-value problems by means of formulas based on Gauss-Legendre quadrature, and combine excellent stability features with the property of superconvergence at the step points."@en ; rdfs:seeAlso , ; rdfs:subClassOf kisao:KISAO_0000064 . kisao:KISAO_0000541 a rdfs:Class ; rdfs:label "beta parameter for stabilized step size control"@en ; rdfs:subClassOf kisao:KISAO_0000242 , kisao:KISAO_0000243 . kisao:KISAO_0000422 a rdfs:Class ; rdfs:label "number of N-way partial least squares regression factors"@en ; rdfs:comment "Parameter of 'N-way partial least squares regression method' [http://identifiers.org/biomodels.kisao/KISAO_0000369] describing the number of factors to compute."@en ; rdfs:subClassOf kisao:KISAO_0000201 . kisao:KISAO_0000819 a rdfs:Class ; rdfs:label "Nr matrix"@en ; rdfs:comment "The Nr matrix of a model."@en ; rdfs:subClassOf kisao:KISAO_0000800 . kisao:KISAO_0000609 a rdfs:Class ; rdfs:label "embedded Runge-Kutta Prince-Dormand (8,9) method"@en ; rdfs:comment "An embedded Runge-Kutta integrator of order 8(9)."@en ; rdfs:subClassOf kisao:KISAO_0000302 . kisao:KISAO_0000467 a rdfs:Class ; rdfs:label "maximum step size"@en ; rdfs:comment "An upper limit, in the units of the bound variable over which a numerical integration is being performed, that an adaptive step size numerical integration algorithm should take."@en ; rdfs:subClassOf kisao:KISAO_0000242 . kisao:KISAO_0000569 a rdfs:Class ; rdfs:label "NLEQ2"@en ; rdfs:comment """Damped Newton-algorithm with rank strategy for systems of highly nonlinear equations. Global Newton method with error oriented convergence criterion; QR-decomposition with subcondition number estimate."""@en ; rdfs:seeAlso , ; rdfs:subClassOf kisao:KISAO_0000408 . kisao:KISAO_0000433 a rdfs:Class ; rdfs:label "CVODE-like method"@en ; rdfs:comment "Solves ODE initial value problems, in real N-space, written as y'=f(t,y), y(t0)=y0. It is capable for stiff and non-stiff systems and uses two different linear multi-step methods, namely the Adam-Moulton [http://identifiers.org/biomodels.kisao/KISAO_0000280] method and the backward differentiation formula [http://identifiers.org/biomodels.kisao/KISAO_0000288]."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000694 . kisao:KISAO_0000563 a rdfs:Class ; rdfs:label "Pahle hybrid Gibson-Bruck Next Reaction method/RK-45 method"@en ; rdfs:comment "Combines a deterministic numerical integration of ODEs with a stochastic simulation algorithm. The whole biochemical network is partitioned into a deterministic and a stochastic subnet internally. The deterministic subnet contains all reactions in which only species with high particle numbers take part. All reactions with at least one low-numbered species are in the stochastic subnet. The partitioning of the biochemical network can change dynamically during the simulation. The reaction probabilities of the stochastic subnet are approximated as constant during one stochastic step. The deterministic subnet is integrated with RK-45. The stochastic subnet is simulated by the Gibson-Bruck Next Reaction Method."@en ; rdfs:seeAlso , , , ; rdfs:subClassOf kisao:KISAO_0000231 . kisao:KISAO_0000801 a rdfs:Class ; rdfs:label "concentration control coefficient matrix (unscaled)"@en ; rdfs:comment "The unscaled concentration control coefficient matrix. The dimensions are species by reactions."@en ; rdfs:subClassOf kisao:KISAO_0000800 . kisao:KISAO_0000383 a rdfs:Class ; rdfs:label "Bader-Deuflhard method"@en ; rdfs:comment "The Bader-Deuflhard method is an extrapolation method based on a semi-implicit discretization [http://identifiers.org/biomodels.kisao/KISAO_0000387]. It is a generalization of the Bulirsch-Stoer algorithm [http://identifiers.org/biomodels.kisao/KISAO_0000379] for solving ordinary differential equations."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000380 . kisao:KISAO_0000397 a rdfs:Class ; rdfs:label "preconditioning technique"@en ; rdfs:comment "Preconditioning is simply a means of transforming the original linear system into one which has the same solution, but which is likely to be easier to solve with an iterative solver."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000000 . kisao:KISAO_0000399 a rdf:Property ; rdfs:label "is used by"@en ; rdfs:comment "A relation between algorithms indicating that one algorithm is used by another one (for example, if the algorithm switches between several algorithms). 'is used by' is inverse of 'uses'."@en ; rdfs:range . kisao:KISAO_0000413 a rdfs:Class ; rdfs:label "exact Newton method"@en ; rdfs:comment "Any of the finite dimensional Newton-type methods [http://identifiers.org/biomodels.kisao/KISAO_0000408] requires the numerical solution of the linear equations F'(x[k])deltax[k]=-F(x[k]). Whenever direct elimination methods are applicable, we speak of exact Newton methods."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000408 . kisao:KISAO_0000612 a rdfs:Class ; rdfs:label "implicit 4th order Runge-Kutta method at Gaussian points"@en ; rdfs:subClassOf kisao:KISAO_0000064 . kisao:KISAO_0000597 a rdfs:Class ; rdfs:label "tolerance"@en ; rdfs:comment "Numeric value specifying the desired tolerance the user wants to achieve. A smaller value means that the prediction is calculated more accurately."@en ; rdfs:subClassOf kisao:KISAO_0000242 . kisao:KISAO_0000663 a rdfs:Class ; rdfs:label "BDD logical model trap space identification method"@en ; rdfs:comment "Method for determining the trap spaces of a regulatory graph using a Binary Decision Diagram (BDD)."@en ; rdfs:subClassOf kisao:KISAO_0000661 . kisao:KISAO_0000517 a rdfs:Class ; rdfs:label "number of generations"@en ; rdfs:comment "The parameter is a positive integer value to determine the number of generations the evolutionary algorithm shall evolve the population."@en ; rdfs:subClassOf kisao:KISAO_0000518 . kisao:KISAO_0000498 a rdfs:Class ; rdfs:label "number of runs"@en ; rdfs:comment "The number of runs that a simulation should perform. Typically used to specify the number of runs for a stochastic simulation."@en ; rdfs:subClassOf kisao:KISAO_0000201 . kisao:KISAO_0000327 a rdfs:Class ; rdfs:label "maximum discrete number"@en ; rdfs:comment "Parameter of 'equation-free probabilistic steady-state approximation' method [http://identifiers.org/biomodels.kisao/KISAO_0000323], which controls the maximum number of molecules of some reactant species in order for the reaction to be considered discrete."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000252 . kisao:KISAO_0000405 a rdfs:Class ; rdfs:label "type of differential equation"@en ; rdfs:subClassOf kisao:KISAO_0000370 . kisao:KISAO_0000552 a rdfs:Class ; rdfs:label "optimization method"@en ; rdfs:comment "Optimization method such as the revised simplex method [http://identifiers.org/biomodels.kisao/KISAO_0000550] or primal-dual interior point method [http://identifiers.org/biomodels.kisao/KISAO_0000551]."@en ; rdfs:subClassOf kisao:KISAO_0000243 . kisao:KISAO_0000424 a rdfs:Class ; rdfs:label "mean-centring of variables"@en ; rdfs:comment "A boolean parameter of the 'hierarchical cluster-based partial least squares regression method' [http://identifiers.org/biomodels.kisao/KISAO_0000417] specifying whether the variables were mean-centred prior to the regression analysis."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000430 . kisao:KISAO_0000623 a rdfs:Class ; rdfs:label "flux balance problem"@en ; rdfs:subClassOf kisao:KISAO_0000370 . kisao:KISAO_0000257 a rdfs:Class ; rdfs:label "surface-bound epsilon"@en ; rdfs:comment "A parameter of 'Brownian diffusion Smoluchowski method' [http://identifiers.org/biomodels.kisao/KISAO_0000057]. Molecules that are bound to a surface are given locations that are extremely close to that surface. However, this position does not need to be exactly at the surface, and in fact it usually cannot be exactly at the surface due to round-off error. The tolerance for how far a surface-bound molecule is allowed to be away from the surface can be set with the epsilon statement."@en ; rdfs:subClassOf kisao:KISAO_0000252 . kisao:KISAO_0000485 a rdfs:Class ; rdfs:label "minimum step size"@en ; rdfs:comment "A lower limit, in the units of the bound variable over which a numerical integration is being performed, that a numerical integration algorithm with variable step size should take."@en ; rdfs:subClassOf kisao:KISAO_0000242 . kisao:KISAO_0000665 a rdfs:Class ; rdfs:label "maximum number of iterations for root finding"@en ; rdfs:subClassOf kisao:KISAO_0000242 . kisao:KISAO_0000091 a rdfs:Class ; rdfs:label "LSODIS"@en ; rdfs:comment "LSODIS is a set of general-purpose FORTRAN routines solver for the initial value problem for ordinary differential equation systems. It is suitable for both stiff and nonstiff systems. LSODIS treat systems in the linearly implicit form A(t,y) dy/dt = g(t,y), A = a square matrix, i.e. with the derivative dy/dt implicit, but linearly so."@en ; rdfs:seeAlso , ; rdfs:subClassOf kisao:KISAO_0000094 . kisao:KISAO_0000064 a rdfs:Class ; rdfs:label "Runge-Kutta based method"@en ; rdfs:comment "A method of numerically integrating ordinary differential equations, which uses a sampling of slopes through an interval and takes a weighted average to determine the right end point. This averaging gives a very accurate approximation."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000377 . kisao:KISAO_0000394 a rdfs:Class ; rdfs:label "quasi-minimal residual variant of biconjugate gradient stabilized method"@en ; rdfs:comment """QMRCGSTAB is a quasi-minimal residual (QMR) variant of the Bi-CGSTAB algorithm [http://identifiers.org/biomodels.kisao/KISAO_0000394] of van der Vorst for solving nonsymmetric linear systems. The motivation for the QMR variant is to obtain smoother convergence behavior of the underlying method. """@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000392 . kisao:KISAO_0000652 a rdfs:Class ; rdfs:label "concentration rate"@en ; rdfs:comment "Rate of a process relative to a volume, such as the rate of a reaction in molar^-1 s^-1."@en ; rdfs:subClassOf kisao:KISAO_0000834 . kisao:KISAO_0000519 a rdfs:Class ; rdfs:label "population size"@en ; rdfs:comment "The parameter is a positive integer value to determine the size of the population, i.e., the number of individuals that survive after each generation."@en ; rdfs:subClassOf kisao:KISAO_0000518 . kisao:KISAO_0000604 a rdfs:Class ; rdfs:label "MSR tolerance"@en ; rdfs:comment "Maximum allowed effect of executing multiple slow reactions per numerical integration of the SDEs."@en ; rdfs:subClassOf kisao:KISAO_0000209 . kisao:KISAO_0000451 a rdfs:Class ; rdfs:label "type of updating policy"@en ; rdfs:comment "A rule to guide the choice of a unique transition at each step used by an 'asynchronous logical model simulation method' [http://identifiers.org/biomodels.kisao/KISAO_0000450]."@en ; rdfs:subClassOf kisao:KISAO_0000097 . kisao:KISAO_0000468 a rdfs:Class ; rdfs:label "maximal timestep method"@en ; rdfs:comment "Hybrid simulation algorithm [http://www.biomodels.net/kisao/KISAO#KISAO_0000352] combining Gibson and Bruck algorithm [http://www.biomodels.net/kisao/KISAO#KISAO_0000027] with the Gillespie tau-leap method [http://www.biomodels.net/kisao/KISAO#KISAO_0000039]."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000352 . kisao:KISAO_0000308 a rdfs:Class ; rdfs:label "MacCormack method"@en ; rdfs:comment "In computational fluid dynamics, the MacCormack method is a widely used discretization scheme for the numerical solution of hyperbolic partial differential equations. This second-order finite difference method [http://identifiers.org/biomodels.kisao/KISAO_0000307] is introduced by R. W. MacCormack in 1969."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000307 . kisao:KISAO_0000280 a rdfs:Class ; rdfs:label "Adams-Moulton method"@en ; rdfs:comment "The (k-1)-step Adams-Moulton method is an implicit linear multistep method that iteratively approximates the solution, y(x) at x = x0+kh, of the initial value problem by yk = yk - 1 + h * ( b0 f(xk,yk) + b1 f(xk - 1,yk - 1) + . . . + bk - 1 f(x1,y1) ), where b1, . . . , bk - 1 are constants."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000289 . kisao:KISAO_0000279 a rdfs:Class ; rdfs:label "Adams-Bashforth method"@en ; rdfs:comment "Given an initial value problem: y' = f(x,y), y(x0) = y0 together with additional starting values y1 = y(x0 + h), . . . , yk-1 = y(x0 + (k-1) h) the k-step Adams-Bashforth method is an explicit linear multistep method that approximates the solution, y(x) at x = x0+kh, of the initial value problem by yk = yk - 1 + h * ( a0 f(xk - 1,yk - 1) + a1 f(xk - 2,yk - 2) + . . . + ak - 1 f(x0,y0) ), where a0, a1, . . . , ak - 1 are constants."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000289 . kisao:KISAO_0000645 a rdfs:Class ; rdfs:label "objective value"@en ; rdfs:comment "Value of an objective function such as of a constraint-based model."@en ; rdfs:subClassOf kisao:KISAO_0000831 . kisao:KISAO_0000204 a rdfs:Class ; rdfs:label "particle number upper limit"@en ; rdfs:comment "This parameter of 'Pahle hybrid method' [http://identifiers.org/biomodels.kisao/KISAO_0000231] is a double value specifying the upper limit for particle numbers. Species with a particle number above this value are considered as having a high particle number. The 'particle number upper limit' cannot be lower than the 'particle number lower limit' [http://identifiers.org/biomodels.kisao/KISAO_0000203]."@en ; rdfs:subClassOf kisao:KISAO_0000252 . kisao:KISAO_0000350 a rdfs:Class ; rdfs:label "probability-weighted dynamic Monte Carlo method"@en ; rdfs:comment "We have developed a probability-weighted DMC method by incorporating the weighted sampling algorithm of equilibrium molecular simulations. This new algorithm samples the slow reactions very efficiently and makes it possible to simulate in a computationally efficient manner the reaction kinetics of physical systems in which the rates of reactions vary by several orders of magnitude."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000333 . kisao:KISAO_0000028 a rdfs:Class ; rdfs:label "slow-scale stochastic simulation algorithm"@en ; rdfs:comment "Attempt to overcome the problem of stiff systems by developing an ''approximate theory that allows one to stochastically advance the system in time by simulating the firings of only the slow reaction events''."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000333 . kisao:KISAO_0000528 a rdfs:Class ; rdfs:label "parsimonious enzyme usage flux balance analysis (minimum sum of absolute fluxes)"@en ; rdfs:comment "Method for determining the smallest flux distribution among all flux distributions that satisfy the constraints of the flux balance analysis (FBA) [http://identifiers.org/biomodels.kisao/KISAO_0000437] model."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000620 . kisao:KISAO_0000579 a rdfs:Class ; rdfs:label "linear MOMA"@en ; rdfs:comment """Linear minimization of metabolic adjustment (MOMA) is an extension of FBA for the prediction of flux distributions in gene knockouts. Linear MOMA employs linear programming to identify the closest point (in terms of its L1 norm) in the permissible flux space of the knockout to the wild-type flux vector by solving the optimization problem Min sum(|fluxAi - fluxBi|)"""@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000593 . kisao:KISAO_0000685 a rdfs:Class ; rdfs:label "biological state optimization method"@en ; rdfs:comment "A method for computing the optimal state of a biological system according to a particular objective."@en ; rdfs:subClassOf kisao:KISAO_0000000 . kisao:KISAO_0000654 a rdfs:Class ; rdfs:label "amount rate"@en ; rdfs:comment "rate of a process in extensive/absolute units such as reactions per second."@en ; rdfs:subClassOf kisao:KISAO_0000834 . kisao:KISAO_0000321 a rdfs:Class ; rdfs:label "Cash-Karp method"@en ; rdfs:comment "An family of explicit Runge-Kutta formulas, which are very efficient for problems with smooth solution as well as problems having rapidly varying solutions. Each member of this family consists of a fifty-order formula that contains embedded formulas of all orders 1 through 4. By computing solutions at several different orders, it is possible to detect sharp fronts or discontinuities before all the function evaluations defining the full Runge-Kutta step have been computed."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000435 . kisao:KISAO_0000558 a rdfs:Class ; rdfs:label "relative steady-state tolerance"@en ; rdfs:comment "Relative error tolerance of the steady-state."@en ; rdfs:subClassOf kisao:KISAO_0000209 . kisao:KISAO_0000366 a rdfs:Class ; rdfs:label "symplecticness"@en ; rdfs:comment "Roughly speaking, ‘symplecticness’ is a characteristic property possessed by the solutions of Hamiltonian problems. A numerical method is called symplectic if, when applied to Hamiltonian problems, it generates numerical solutions which inherit the property of symplecticness (phase volume preservation)."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000097 . kisao:KISAO_0000231 a rdfs:Class ; rdfs:label "Pahle hybrid method"@en ; rdfs:comment "The hybrid method combines the stochastic 'Gibson-Bruck's next reaction method' [http://identifiers.org/biomodels.kisao/KISAO_0000027] with different algorithms for the numerical integration of ODEs [http://identifiers.org/biomodels.kisao/KISAO_0000245 some http://identifiers.org/biomodels.kisao/KISAO_0000374]. The biochemical network is dynamically partitioned into a deterministic and a stochastic subnet depending on the current particle numbers in the system. The user can define limits for when a particle number should be considered low or high. The stochastic subnet contains reactions involving low numbered species as substrate or product. All the other reactions form the deterministic subnet. The two subnets are then simulated in parallel using the stochastic and deterministic solver, respectively. The reaction probabilities in the stochastic subnet are approximated as constant between two stochastic reaction events."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000352 . kisao:KISAO_0000811 a rdfs:Class ; rdfs:label "stoichiometry matrix"@en ; rdfs:comment "The (full) stoichiometry matrix. The dimensions are species by reactions."@en ; rdfs:subClassOf kisao:KISAO_0000800 . kisao:KISAO_0000478 a rdfs:Class ; rdfs:label "preconditioner"@en ; rdfs:comment "the preconditioner, if any, used by the solver when using a GMRES, BiCGStab or TFQMR linear solver during a Newton iteration."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000201 . kisao:KISAO_0000627 a rdfs:Class ; rdfs:label "diagonal approximate Jacobian solver"@en ; rdfs:subClassOf kisao:KISAO_0000624 . kisao:KISAO_0000316 a rdfs:Class ; rdfs:label "enhanced Greens function reaction dynamics"@en ; rdfs:comment "GFRD [http://identifiers.org/biomodels.kisao/KISAO_0000058] decomposes the multi­body reaction diffusion problem to a set of single and two body problems. Analytical solutions for two body reaction diffusion are available via Smoluchowski equation. eGFRD allows to solve each sub­problem asynchronously by introducing the concept of first passage processes."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000056 . kisao:KISAO_0000107 a rdfs:Class ; rdfs:label "progression with adaptive time step"@en ; rdfs:comment "Algorithm, possessing this characteristic, does not use fixed time steps to update the state of a system during the whole simulation, but on the contrary adapts the length of the time steps to the local situation."@en ; rdfs:subClassOf kisao:KISAO_0000100 . kisao:KISAO_0000591 a rdfs:Class ; rdfs:label "mdFBA"@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000437 . kisao:KISAO_0000260 a rdfs:Class ; rdfs:label "virtual box size"@en ; rdfs:comment "Target size of virtual boxes for 'Brownian diffusion Smoluchowski method' [http://identifiers.org/biomodels.kisao/KISAO_0000057]."@en ; rdfs:subClassOf kisao:KISAO_0000252 . kisao:KISAO_0000000 a rdfs:Class ; rdfs:label "modelling and simulation algorithm"@en ; rdfs:comment "Algorithm used to instantiate a simulation from a mathematical model."@en . kisao:KISAO_0000834 a rdfs:Class ; rdfs:label "rate of change"@en ; rdfs:comment "The rate of change of one variable with respect to a second variable."@en ; rdfs:subClassOf kisao:KISAO_0000831 . kisao:KISAO_0000377 a rdfs:Class ; rdfs:label "one-step method"@en ; rdfs:comment "A numerical method for differential equations which uses one starting value at each step."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000694 . kisao:KISAO_0000346 a rdfs:Class ; rdfs:label "mesh-based geometry handling"@en ; rdfs:comment "In most large-scale numerical simulations of physical phenomena, a large percentage of the overall computational effort is expended on technical details connected with meshing. These details include, in particular, grid generation, mesh adaptation to domain geometry, element or cell connectivity, grid motion and separation to model fracture, fragmentation, free surfaces, etc."@en ; rdfs:subClassOf kisao:KISAO_0000311 . kisao:KISAO_0000429 a rdfs:Class ; rdfs:label "clusterization parameter"@en ; rdfs:comment "Parameter used by algorithms performing clusterization."@en ; rdfs:subClassOf kisao:KISAO_0000201 . kisao:KISAO_0000216 a rdfs:Class ; rdfs:label "use reduced model"@en ; rdfs:comment """Boolean value which indicates whether the simulation/analysis should be performed using the complete model or an equivalent reduced model. Reduced models can be determined in many ways such as using mass conservation laws."""@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000243 . kisao:KISAO_0000409 a rdfs:Class ; rdfs:label "ordinary Newton method"@en ; rdfs:comment "A 'Newton-type method' [http://identifiers.org/biomodels.kisao/KISAO_0000408] which solves the general nonlinear problem F(x)=0 by applying successive linearization F'(x[k])deltax[k]=-F(x[k]), x[k+1]=x[k]+deltax[k], k=0,1,..."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000408 . kisao:KISAO_0000573 a rdfs:Class ; rdfs:label "probabilistic logical model simulation method"@en ; rdfs:comment "Qualitative (logical) models specify the evolution rules of their components. Probabilistic networks allow for specifying more than one transition function per variable/gene. Each of these functions has a probability to be chosen, where the probabilities of all functions for one variable sum up to 1. Transitions are performed synchronously by choosing one transition function for each gene according to their probabilities and applying them to the current state."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000319 , kisao:KISAO_0000448 . kisao:KISAO_0000324 a rdfs:Class ; rdfs:label "nested stochastic simulation algorithm"@en ; rdfs:comment "This multiscale method is a small modification of the Gillespie's direct method [http://identifiers.org/biomodels.kisao/KISAO_0000029], in the form of a nested SSA, with inner loops for the fast reactions, and outer loop for the slow reactions. The number of groups can be more than two, and the grouping into fast and slow variables can be done dynamically in an adaptive version of the scheme."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000333 . kisao:KISAO_0000616 a rdfs:Class ; rdfs:label "semi-implicit regular grid finite volume method with a fixed time step"@en ; rdfs:subClassOf kisao:KISAO_0000285 . kisao:KISAO_0000388 a rdfs:Class ; rdfs:label "minimal residual method"@en ; rdfs:comment "The 'minimal residual method' is an algorithm for the numerical solution of indefinite symmertic systems of linear equations."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000354 . kisao:KISAO_0000432 a rdfs:Class ; rdfs:label "IDA-like method"@en ; rdfs:comment "Solves real differential-algebraic systems in N-space, in the general form F(t,y,y')=0, y(t0)=y0, y'(t0)=y'0. At each step, a Newton iteration [http://identifiers.org/biomodels.kisao/KISAO_0000408] leads to linear systems Jx=b, which are solved by one of five methods - two direct (dense or band; serial version only) and three Krylov [http://identifiers.org/biomodels.kisao/KISAO_0000354] (GMRES [http://identifiers.org/biomodels.kisao/KISAO_0000353], BiCGStab [http://identifiers.org/biomodels.kisao/KISAO_0000392], or TFQMR [http://identifiers.org/biomodels.kisao/KISAO_0000396])."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000699 . kisao:KISAO_0000353 a rdfs:Class ; rdfs:label "generalized minimal residual algorithm"@en ; rdfs:comment "An iterative method for solving linear systems, which has the property of minimizing at every step the norm of the residual vector over a Krylov subspace. The generalized minimal residual method extends the minimal residual method (MINRES) [http://identifiers.org/biomodels.kisao/KISAO_0000388], which is only applicable to symmetric systems, to non-symmetric systems."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000354 . kisao:KISAO_0000296 a rdfs:Class ; rdfs:label "Hammer-Hollingsworth method"@en ; rdfs:comment "The numerical integration of ordinary differential equations by the use of Gaussian quadrature methods."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000064 . kisao:KISAO_0000454 a rdfs:Class ; rdfs:label "constant updating policy"@en ; rdfs:comment "An updating policy that chooses a transition in a constant way."@en ; rdfs:subClassOf kisao:KISAO_0000453 . kisao:KISAO_0000619 a rdfs:Class ; rdfs:label "emc-sim"@en ; rdfs:comment "A variant of the stochastic simulation algorithm (SSA) in which the time to the next reaction is a constant equal to 1 time unit. In this method, the next reaction time is deterministic rather than stochastic as in SSA."@en ; rdfs:subClassOf kisao:KISAO_0000335 . kisao:KISAO_0000331 a rdfs:Class ; rdfs:label "exact R-leaping algorithm"@en ; rdfs:comment "We present a SSA which, similar to R-leap [http://identifiers.org/biomodels.kisao/KISAO_0000330], accelerates SSA [http://identifiers.org/biomodels.kisao/KISAO_0000029] by executing multiple reactions per algorithmic step, but which samples the reactant trajectories from the same probability distribution as the SSA. This 'exact R-leap' or 'ER-leap' algorithm is a modification of the R-leap algorithm which is both exact and capable of substantial speed-up over SSA."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000621 . kisao:KISAO_0000276 a rdfs:Class ; rdfs:label "Gill method"@en ; rdfs:comment "Gill's fourth order method is a Runge-Kutta method for approximating the solution of the initial value problem y'(x) = f(x,y); y(x0) = y0 which evaluates the integrand,f(x,y), four times per step. This method is a fourth order procedure for which Richardson extrapolation can be used."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000064 . kisao:KISAO_0000407 a rdfs:Class ; rdfs:label "steady state root-finding method"@en ; rdfs:comment "Method for finding the root of a function (f(x) = 0)."@en ; rdfs:subClassOf kisao:KISAO_0000630 . kisao:KISAO_0000487 a rdfs:Class ; rdfs:label "minimum damping"@en ; rdfs:comment "The damping factor is a variable for at least some steady state algorithms: roadrunner allows you to set the minimum value for this."@en ; rdfs:subClassOf kisao:KISAO_0000201 . kisao:KISAO_0000608 a rdfs:Class ; rdfs:label "hierarchical flux balance analysis"@en ; rdfs:comment "Method for constraint-based simulation of hierarchically organized models, such as a model of a cellular population where each cell in the population is represented by the same species and reactions."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000437 . kisao:KISAO_0000328 a rdfs:Class ; rdfs:label "minimum fast rate"@en ; rdfs:comment "Parameter of 'equation-free probabilistic steady-state approximation' method [http://identifiers.org/biomodels.kisao/KISAO_0000323], which controls the minimum rate of the reaction in order for it to be considered fast."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000252 . kisao:KISAO_0000854 a rdfs:Class ; rdfs:label "length ignoring NaN"@en ; rdfs:comment "The number of elements of a set of values, ignoring Nan entries."@en ; rdfs:subClassOf kisao:KISAO_0000824 . kisao:KISAO_0000504 a rdfs:Class ; rdfs:label "random search"@en ; rdfs:comment """Random search is an optimization method that attempts to find the optimum by testing the objective function's value on a series of combinations of random values of the adjustable parameters. The random values are generated complying with any boundaries selected by the user, furthermore, any combinations of parameter values that do not fulfill constraints on the variables are excluded. This means that the method is capable of handling bounds on the adjustable parameters and fulfilling constraints. For infinite number of iterations this method is guaranteed to find the global optimum of the objective function. In general one is interested in processing a very large number of iterations."""@en ; rdfs:subClassOf kisao:KISAO_0000472 . kisao:KISAO_0000839 a rdfs:Class ; rdfs:label "temperature"@en ; rdfs:comment "The intensive quantity temperature."@en ; rdfs:subClassOf kisao:KISAO_0000831 . kisao:KISAO_0000496 a rdfs:Class ; rdfs:label "CVODES"@en ; rdfs:comment "CVODES is a solver for stiff and nonstiff ODE systems (initial value problem) given in explicit form y’ = f(t,y,p) with sensitivity analysis capabilities (both forward and adjoint modes)."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000433 . kisao:KISAO_0000584 a rdfs:Class ; rdfs:label "initial order"@en ; rdfs:comment "Initial order of method."@en ; rdfs:subClassOf kisao:KISAO_0000594 . kisao:KISAO_0000082 a rdfs:Class ; rdfs:label "k-alpha leaping method"@en ; rdfs:comment "Alternative to the tau-leaping [http://identifiers.org/biomodels.kisao/KISAO_0000039], where one leaps a fixed number of reaction-events."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000621 . kisao:KISAO_0000687 a rdfs:Class ; rdfs:label "Max-min Driving Force method"@en ; rdfs:comment "For a given metabolic network model, the MDF method determines plausible metabolite concentrations and thermodynamic forces. Flux directions, equilibrium constants (or equivalently, standard Gibbs free energies of reactions) and admissible metabolite concentration ranges are given as input data. The method applies the principle that low thermodynamic forces must be avoided, and maximizes the minimum thermodynamic force across the entire network."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000685 . kisao:KISAO_0000697 a rdfs:Class ; rdfs:label "SDE solver"@en ; rdfs:comment "An SDE solver is the general category of packages that provide stochastic solutions to a system of differential equations with propensities."@en ; rdfs:subClassOf kisao:KISAO_0000000 . kisao:KISAO_0000342 a rdfs:Class ; rdfs:label "level set method"@en ; rdfs:comment "An algorithm for moving surfaces under their curvature. This algorithm rely on numerically solving Hamilton-Jacobi equations with viscous terms, using approximation techniques from hyperbolic conservation laws."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000369 . kisao:KISAO_0000522 a rdfs:Class ; rdfs:label "start temperature"@en ; rdfs:comment "Initial temperature of the system. The higher the temperature, the larger the probability that a global optimum is found. Note that the temperature should be very high in the beginning of the method (the system should be above the \"melting\" temperature). This value has the same units as the objective function, so what represents \"high\" is different from problem to problem."@en ; rdfs:subClassOf kisao:KISAO_0000521 . kisao:KISAO_0000676 a rdfs:Class ; rdfs:label "degree of linearity"@en ; rdfs:comment "The degree of linearity of a system."@en ; rdfs:subClassOf kisao:KISAO_0000243 . kisao:KISAO_0000480 a rdfs:Class ; rdfs:label "lower half-bandwidth"@en ; rdfs:comment "the lower half-bandwidth value used by the Banded linear solver or preconditioner (a value between 0 and n-1 with n the number of ODEs/DAEs in the model)."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000482 . kisao:KISAO_0000099 a rdfs:Class ; rdfs:label "type of system behaviour"@en ; rdfs:comment "A characteristic describing the rules the algorithm uses to simulate the temporal evolution of a system, specifically whether or not the final state is uniquely determined from a precise initial state."@en ; rdfs:subClassOf kisao:KISAO_0000097 . kisao:KISAO_0000809 a rdfs:Class ; rdfs:label "reduced Jacobian matrix"@en ; rdfs:comment "The reduced Jacobian matrix. The dimensions are species by species."@en ; rdfs:subClassOf kisao:KISAO_0000800 . kisao:KISAO_0000404 a rdfs:Class ; rdfs:label "symmetricity of matrix"@en ; rdfs:comment "In linear algebra, a symmetric matrix is a square matrix that is equal to its transpose."@en ; rdfs:subClassOf kisao:KISAO_0000370 . kisao:KISAO_0000357 a rdfs:Class ; rdfs:label "conjugate gradient method"@en ; rdfs:comment "Conjugate gradient method is an algorithm for the numerical solution of particular systems of linear equations, namely those whose matrix is symmetric and positive-definite. The conjugate gradient method is an iterative method, so it can be applied to sparse systems that are too large to be handled by direct methods. Such systems often arise when numerically solving partial differential equations."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000354 . kisao:KISAO_0000476 a rdfs:Class ; rdfs:label "iteration type"@en ; rdfs:comment "the type of iteration used by the solver"@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000201 . kisao:KISAO_0000071 a rdfs:Class ; rdfs:label "LSODE"@en ; rdfs:comment "LSODE solves stiff and nonstiff systems of the form dy/dt = f. In the stiff case, it treats the Jacobian matrix sf/dy as either a dense (full) or a banded matrix, and as either user-supplied or internally approximated by difference quotients. It uses Adams methods (predictor-corrector) [http://identifiers.org/biomodels.kisao/KISAO_0000364] in the nonstiff case, and Backward Differentiation Formula (BDF) methods (the Gear methods) [http://identifiers.org/biomodels.kisao/KISAO_0000288] in the stiff case."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000094 . kisao:KISAO_0000580 a rdfs:Class ; rdfs:label "ROOM"@en ; rdfs:comment "Constraint-based algorithm for predicting the metabolic steady state after gene knockouts which aims to minimize the number of significant flux changes (hence on/off) with respect to the wild type."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000622 , kisao:KISAO_0000630 . kisao:KISAO_0000242 a rdfs:Class ; rdfs:label "error control parameter"@en ; rdfs:comment "Parameter controlling method accuracy."@en ; rdfs:subClassOf kisao:KISAO_0000201 . kisao:KISAO_0000537 a rdfs:Class ; rdfs:label "explicit Runge-Kutta method of order 3(2)"@en ; rdfs:comment "RK23 uses the Bogacki-Shampine pair of formulas [1]. The error is controlled assuming accuracy of the second-order method, but steps are taken using the third-order accurate formula (local extrapolation is done). A cubic Hermite polynomial is used for the dense output."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000064 . kisao:KISAO_0000473 a rdfs:Class ; rdfs:label "Bayesian inference algorithm"@en ; rdfs:comment "A bayesian inference algorithm calculates a posterior probability distribution from a prior probability distribution and some additional evidence in the form of a likelyhood function."@en ; rdfs:seeAlso , ; rdfs:subClassOf kisao:KISAO_0000000 . kisao:KISAO_0000484 a rdfs:Class ; rdfs:label "maximum order"@en ; rdfs:comment "Maximum order of method. For example, in Roadrunner it can be used for two parameters that one can set for deterministic runs: 'maximum_bdf_order' and 'maximum_adams_order'."@en ; rdfs:subClassOf kisao:KISAO_0000594 . kisao:KISAO_0000254 a rdfs:Class ; rdfs:label "Brownian diffusion accuracy"@en ; rdfs:comment "Accuracy code of 'Brownian diffusion Smoluchowski method' [http://identifiers.org/biomodels.kisao/KISAO_0000057], which sets which neighbouring boxes are checked for potential bi-molecular reactions. Consider the reaction A + B -> C and suppose that A and B are within a binding radius of each other. This reaction will always be performed if A and B are in the same virtual box. If accuracy is set to at least 3, then it will also occur if A and B are in nearest-neighbour virtual boxes. If it is at least 7, then the reaction will happen if they are in nearest-neighbour boxes that are separated by periodic boundary conditions. And if it is 9 or 10, then all edge and corner boxes are checked for reactions, which means that no potential reactions are overlooked."@en ; rdfs:subClassOf kisao:KISAO_0000242 . kisao:KISAO_0000638 a rdfs:Class ; rdfs:label "level"@en ; rdfs:comment "A level such as of a qualitative variable."@en ; rdfs:subClassOf kisao:KISAO_0000831 . kisao:KISAO_0000058 a rdfs:Class ; rdfs:label "Greens function reaction dynamics"@en ; rdfs:comment "Method that simulates biochemical networks on particle level. It considers both changes in time and space by ''exploiting both the exact solution of the Smoluchowski Equation to set up an event-driven algorithm'' which allows for large jumps in time when the considered particles are far away from each other [in space] and thus cannot react. GFRD combines the propagation of particles in space with the reactions taking place between them in one simulation step."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000056 . kisao:KISAO_0000812 a rdfs:Class ; rdfs:label "Jacobian matrix"@en ; rdfs:comment "The (full) Jacobian matrix. The dimensions are species by species."@en ; rdfs:subClassOf kisao:KISAO_0000800 . kisao:KISAO_0000500 a rdfs:Class ; rdfs:label "SOA-DFBA"@en ; rdfs:comment "Dynamic Flux Balance Analysis (DFBA) [http://identifiers.org/biomodels.kisao/KISAO_0000499] couples flux balance analysis (FBA) [http://identifiers.org/biomodels.kisao/KISAO_0000437] model approaches with dynamic model approaches. The static optimization approach (SOA) uses the Euler forward method [http://identifiers.org/biomodels.kisao/KISAO_0000030], solving the embedded LPs at each time step. The FBA fluxes are assumed to be constant during the time step."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000499 . kisao:KISAO_0000559 a rdfs:Class ; rdfs:label "initial step size"@en ; rdfs:comment "Initial time step size."@en ; rdfs:subClassOf kisao:KISAO_0000242 . kisao:KISAO_0000238 a rdfs:Class ; rdfs:label "type of method"@en ; rdfs:comment "A characteristic describing the way the method finds a solution, specifically whether it solves an equation involving only the current state of the system (explicit) or both the current and the later one (implicit). "@en ; rdfs:subClassOf kisao:KISAO_0000097 . kisao:KISAO_0000305 a rdfs:Class ; rdfs:label "Verner method"@en ; rdfs:comment "The first high order (6(5)) embedded Runge-Kutta formulas that avoid the drawback of giving identically zero error estimates for quadrature problems y' = f(x) were constructed by Verner in 1978."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000302 . kisao:KISAO_0000511 a rdfs:Class ; rdfs:label "steepest descent"@en ; rdfs:comment "Steepest descent is an optimization method that follows the direction of steepest descent on the hyper-surface of the objective function to find a local minimum. The direction of steepest descent is defined by the negative of the gradient of the objective function."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000471 . kisao:KISAO_0000548 a rdfs:Class ; rdfs:label "quadratic programming"@en ; rdfs:comment "Process of solving a quadratic optimization problem."@en ; rdfs:subClassOf kisao:KISAO_0000549 . kisao:KISAO_0000019 a rdfs:Class ; rdfs:label "CVODE"@en ; rdfs:comment "The CVODE is a package written in C that solves ODE initial value problems, in real N-space, written as y'=f(t,y), y(t0)=y0. It is capable for stiff and non-stiff systems and uses two different linear multi-step methods, namely the Adam-Moulton [http://identifiers.org/biomodels.kisao/KISAO_0000280] method and the backward differentiation formula [http://identifiers.org/biomodels.kisao/KISAO_0000288]."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000433 . kisao:KISAO_0000808 a rdfs:Class ; rdfs:label "reduced stoichiometry matrix"@en ; rdfs:comment "The reduced stoichiometry matrix. The dimensions are species by reactions."@en ; rdfs:subClassOf kisao:KISAO_0000800 . kisao:KISAO_0000410 a rdfs:Class ; rdfs:label "simplified Newton method"@en ; rdfs:comment "A 'Newton-type method' [http://identifiers.org/biomodels.kisao/KISAO_0000408] which is characterized by keeping the initial derivative throughout the whole iteration: F'(x[0])deltax[k]=-F(x[k]), x[k+1]=x[k]+deltax[k], k=0,1,..."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000408 . kisao:KISAO_0000859 a rdfs:Class ; rdfs:label "variance"@en ; rdfs:comment "The variance of a set of values. If the values contain NaN the variance is NaN."@en ; rdfs:subClassOf kisao:KISAO_0000824 . kisao:KISAO_0000491 a rdfs:Class ; rdfs:label "discrete event simulation algorithm"@en ; rdfs:comment "Discrete Event Simulation algorithm refers to the simulation of systems whose (countable) discrete states change over time and are event-driven."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000000 . kisao:KISAO_0000509 a rdfs:Class ; rdfs:label "evolutionary strategy"@en ; rdfs:comment "Evolutionary Strategies with Stochastic Ranking (SRES) is similar to Evolutionary Programming. However, a parent has multiple offsprings during each generation. Each offspring will contain a recombination of genes with another parent and additional mutations. The algorithm assures that each parameter value will be within its boundaries. But constraints to the solutions may be violated."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000508 . kisao:KISAO_0000596 a rdfs:Class ; rdfs:label "srFBA"@en ; rdfs:comment "Method for predicting steady-state metabolic fluxes under patterns of the regulation of gene expression"@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000437 , kisao:KISAO_0000595 . kisao:KISAO_0000421 a rdfs:Class ; rdfs:label "type of validation"@en ; rdfs:comment "Parameter of 'partial least squares regression method' [http://identifiers.org/biomodels.kisao/KISAO_0000416] describing how validation is performed. Possible values include cross-validation and test set validation."@en ; rdfs:subClassOf kisao:KISAO_0000201 . kisao:KISAO_0000516 a rdfs:Class ; rdfs:label "Hooke&Jeeves"@en ; rdfs:comment "The method of Hooke and Jeeves is a direct search algorithm that searches for the minimum of a nonlinear function without requiring (or attempting to calculate) derivatives of the function. Instead it is based on a heuristic that suggests a descent direction using the values of the function calculated in a number of previous iterations."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000471 . kisao:KISAO_0000205 a rdfs:Class ; rdfs:label "partitioning interval"@en ; rdfs:comment "This positive integer value specifies after how many steps the internal partitioning of the system should be recalculated."@en ; rdfs:subClassOf kisao:KISAO_0000252 . kisao:KISAO_0000527 a rdfs:Class ; rdfs:label "geometric flux balance analysis"@en ; rdfs:comment "Method for determining the central flux distribution among all flux distributions that satisfy the constraints of the flux balance analysis (FBA) [http://identifiers.org/biomodels.kisao/KISAO_0000437] model."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000437 . kisao:KISAO_0000261 a rdfs:Class ; rdfs:label "Euler method"@en ; rdfs:comment "The Euler method, named after Leonhard Euler, is a first-order numerical procedure for solving ordinary differential equations (ODEs) with a given initial value."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000377 . kisao:KISAO_0000285 a rdfs:Class ; rdfs:label "finite volume method"@en ; rdfs:comment "The finite volume method is a method for representing and evaluating partial differential equations in the form of algebraic equations, which attempts to emulate continuous conservation laws of physics."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000369 . kisao:KISAO_0000469 a rdfs:Class ; rdfs:label "maximal timestep"@en ; rdfs:comment "Key parameter of the 'maximal timestep method' [http://www.biomodels.net/kisao/KISAO#KISAO_0000468]. If Gillespie [http://www.biomodels.net/kisao/KISAO#KISAO_0000027] waiting time is longer than maximal timestep, slow reaction is not fired and tau-leap [http://www.biomodels.net/kisao/KISAO#KISAO_0000039] step is executed for fast reactions. Otherwise, slow reaction is fired and tau-leap [http://www.biomodels.net/kisao/KISAO#KISAO_0000039] is executed with shorter time step."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000243 . kisao:KISAO_0000417 a rdfs:Class ; rdfs:label "hierarchical cluster-based partial least squares regression method"@en ; rdfs:comment "Requested by Kristin Tøndel on Thursday, October 13, 2011 11:13:17 AM."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000423 . kisao:KISAO_0000605 a rdfs:Class ; rdfs:label "SDE tolerance"@en ; rdfs:comment "Stochastic differential equation tolerance"@en ; rdfs:subClassOf kisao:KISAO_0000209 . kisao:KISAO_0000087 a rdfs:Class ; rdfs:label "Dormand-Prince method"@en ; rdfs:comment """Dormand-Prince is an explicit method for the numerical integration of ODES with a given initial value. It is an 'embedded Runge-Kutta method' [http://identifiers.org/biomodels.kisao/KISAO_0000302] RK5 (4) which (a) has a 'small' principal truncation term in the Fifth order and (b) has an extended region of absolute stability."""@en ; rdfs:seeAlso , ; rdfs:subClassOf kisao:KISAO_0000435 . kisao:KISAO_0000631 a rdfs:Class ; rdfs:label "iterative root-finding method"@en ; rdfs:comment "Iterative method for finding the root of a function (f(x) = 0)."@en ; rdfs:subClassOf kisao:KISAO_0000407 . kisao:KISAO_0000646 a rdfs:Class ; rdfs:label "propensity"@en ; rdfs:comment "Tendency of an event such as of the firing of a reaction in the stochastic simulation algorithm (SSA, KISAO_0000029)."@en ; rdfs:subClassOf kisao:KISAO_0000831 . kisao:KISAO_0000818 a rdfs:Class ; rdfs:label "L0 matrix"@en ; rdfs:comment "The L0 matrix of a model."@en ; rdfs:subClassOf kisao:KISAO_0000800 . kisao:KISAO_0000472 a rdfs:Class ; rdfs:label "global optimization algorithm"@en ; rdfs:comment "A global optimization algorithm is an optimization algorithm [http://www.biomodels.net/kisao/KISAO#KISAO_0000470] that tries to find the global optimum of a function. If a function has several minima/maxima with in the allowed range of variable values, the global minimum/maximum is the one with the smallest/largest function value."@en ; rdfs:subClassOf kisao:KISAO_0000470 . kisao:KISAO_0000428 a rdfs:Class ; rdfs:label "matrix for clusterization"@en ; rdfs:comment "A matrix to do the clustering in 'hierarchical cluster-based partial least squares regression method' [http://identifiers.org/biomodels.kisao/KISAO_0000417]."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000429 . kisao:KISAO_0000686 a rdfs:Class ; rdfs:label "Enzyme Cost Minimization"@en ; rdfs:comment "For a given metabolic network model, the Enzyme Cost Minimization method determines plausible metabolite and enzyme concentrations (which determine thermodynamic forces and enzyme catalytic rates). Fluxes, enzyme kinetic constants, admissible metabolite concentration ranges, and enzyme cost weights (e.g. enzyme molecular masses) are given as input data. The method applies the principle that high enzyme (or enzyme plus metabolite) concentrations must be avoided, and maximizes a weighted sum of enzyme and metabolite concentrations."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000685 . kisao:KISAO_0000671 a rdfs:Class ; rdfs:label "use stiff method"@en ; rdfs:comment "Specifies whether the integrator attempts to solve stiff equations."@en ; rdfs:subClassOf kisao:KISAO_0000243 . kisao:KISAO_0000235 a rdfs:Class ; rdfs:label "type of solution"@en ; rdfs:comment "A characteristic describing the type of the solution produced by the method, specifically whether it is exact or approximate."@en ; rdfs:subClassOf kisao:KISAO_0000097 . kisao:KISAO_0000698 a rdfs:Class ; rdfs:label "particle coordinates"@en ; rdfs:comment "The set of coordinates for all particles of these entities."@en ; rdfs:subClassOf kisao:KISAO_0000831 . kisao:KISAO_0000804 a rdfs:Class ; rdfs:label "elasticity matrix (unscaled)"@en ; rdfs:comment "The unscaled elasticity matrix. The dimensions are reactions by species."@en ; rdfs:subClassOf kisao:KISAO_0000800 . kisao:KISAO_0000829 a rdfs:Class ; rdfs:label "minimum ignoring NaN"@en ; rdfs:comment "The minimum value of a set of values, ignoring NaN entries."@en ; rdfs:subClassOf kisao:KISAO_0000824 . kisao:KISAO_0000339 a rdfs:Class ; rdfs:label "p-version of the finite element method"@en ; rdfs:comment "The p version of 'finite element method' [http://identifiers.org/biomodels.kisao/KISAO_0000337] uses a fixed mesh but increases the polynomial degree p to increase accuracy. Can be considered as a special case of the h-p version [http://identifiers.org/biomodels.kisao/KISAO_0000340]."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000337 . kisao:KISAO_0000649 a rdfs:Class ; rdfs:label "shadow price"@en ; rdfs:comment "Change, per infinitesimal unit of the constraint, in the optimal value of the objective function of an optimization problem obtained by relaxing the constraint."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000650 . kisao:KISAO_0000395 a rdfs:Class ; rdfs:label "improved biconjugate gradient method"@en ; rdfs:comment """An 'improved biconjugate gradient method' branch contains algorithms which can be viewed as improvements over some of drawbacks of BCG [http://identifiers.org/biomodels.kisao/KISAO_0000358], such as (1) the need for matrix-vector multiplications with A^T (which can be inconvenient as well as doubling the number of matrix-vector multiplications compared to CG [http://identifiers.org/biomodels.kisao/KISAO_0000357] for each increase in the degree of the underlying Krylov subspace), (2) the possibility of breakdowns and (3) erratic convergence behavior. """@en ; rdfs:subClassOf kisao:KISAO_0000354 . kisao:KISAO_0000447 a rdfs:Class ; rdfs:label "COAST"@en ; rdfs:comment "An approximative algorithm for stochastic simulations of chemical reaction systems based on three different modeling levels: for small numbers of particles an exact [http://identifiers.org/biomodels.kisao/KISAO_0000236] stochastic [http://identifiers.org/biomodels.kisao/KISAO_0000104] model; for intermediate numbers an approximative [http://identifiers.org/biomodels.kisao/KISAO_0000237], but computationally more efficient stochastic [http://identifiers.org/biomodels.kisao/KISAO_0000104] model based on discrete Gaussian distributions; and for large numbers the deterministic [http://identifiers.org/biomodels.kisao/KISAO_0000103] reaction kinetics. In every simulation time step, the subdivision of the reaction channels into the three different modeling levels is done automatically, where all approximations applied can be controlled by a single error parameter for which an appropriate value can easily be found."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000352 . kisao:KISAO_0000635 a rdfs:Class ; rdfs:label "unscaled property"@en ; rdfs:subClassOf kisao:KISAO_0000820 . kisao:KISAO_0000320 a rdfs:Class ; rdfs:label "BioRica hybrid method"@en ; rdfs:comment "The simulation schema for a given BioRica node is given by a hybrid algorithm that deals with continuous time and allows for discrete events that roll back the time according to these discrete interruptions."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000352 . kisao:KISAO_0000521 a rdfs:Class ; rdfs:label "simulated annealing parameter"@en ; rdfs:subClassOf kisao:KISAO_0000201 . kisao:KISAO_0000658 a rdfs:Class ; rdfs:label "logical model analysis method"@en ; rdfs:comment "A method for analyzing a logical model, such as finding its fixed points."@en ; rdfs:subClassOf kisao:KISAO_0000000 . kisao:KISAO_0000675 a rdfs:Class ; rdfs:label "Broyden method"@en ; rdfs:comment "Family of Quasi-Newton methods for finding roots in k variables originally described by C. G. Broyden in 1965."@en ; rdfs:subClassOf kisao:KISAO_0000243 . kisao:KISAO_0000365 a rdfs:Class ; rdfs:label "NDSolve method"@en ; rdfs:comment "The Mathematica computation system function NDSolve is a general numerical differential equation solver. It can handle a wide range of ordinary differential equations as well as some partial differential equations. NDSolve can also solve some differential-algebraic equations, which are typically a mix of differential and algebraic equations."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000352 . kisao:KISAO_0000650 a rdfs:Class ; rdfs:label "sensitivity"@en ; rdfs:comment "The sensitivity of a variable to another variable, such as the derivative a variable with respect to another."@en ; rdfs:subClassOf kisao:KISAO_0000831 . kisao:KISAO_0000384 a rdfs:Class ; rdfs:label "semi-implicit midpoint rule"@en ; rdfs:comment "A semi-implicit version of the midpoint method that has an even error series [http://identifiers.org/biomodels.kisao/KISAO_0000381]."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000064 . kisao:KISAO_0000642 a rdfs:Class ; rdfs:label "minimum flux"@en ; rdfs:comment "Minimum possible flux such as computed by flux variability analysis (FVA, KISAO_0000526)."@en ; rdfs:subClassOf kisao:KISAO_0000639 . kisao:KISAO_0000302 a rdfs:Class ; rdfs:label "embedded Runge-Kutta method"@en ; rdfs:comment "An embedded Runge-Kutta method is a method in which two Runge-Kutta estimates are obtained using the same auxiliary functions ki but with a different linear combination of these functions so that one estimate has an order one greater than the other."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000064 . kisao:KISAO_0000830 a rdfs:Class ; rdfs:label "maximum"@en ; rdfs:comment "The maximum of a set of values. If the values contain NaN the maximum is NaN."@en ; rdfs:subClassOf kisao:KISAO_0000824 . kisao:KISAO_0000660 a rdfs:Class ; rdfs:label "logical model stable state search method"@en ; rdfs:comment "Method for determining the stable states of a regulatory graph."@en ; rdfs:subClassOf kisao:KISAO_0000658 . kisao:KISAO_0000601 a rdfs:Class ; rdfs:label "number of trials"@en ; rdfs:comment "Number of multiple trials (e.g., of a scatter search method)."@en ; rdfs:subClassOf kisao:KISAO_0000244 . kisao:KISAO_0000104 a rdfs:Class ; rdfs:label "stochastic system behaviour"@en ; rdfs:comment "Algorithm, possessing this characteristic, simulates the temporal evolution of a system using probabilistic rules, so that between two simulations, the same precise initial state may result in a different final state."@en ; rdfs:subClassOf kisao:KISAO_0000099 . kisao:KISAO_0000290 a rdfs:Class ; rdfs:label "Merson method"@en ; rdfs:comment "A five-stage Runge-Kutta method with fourth-order accuracy."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000302 . kisao:KISAO_0000249 a rdfs:Class ; rdfs:label "critical firing threshold"@en ; rdfs:comment "The 'nonnegative Poisson tau-leaping method' [http://identifiers.org/biomodels.kisao/KISAO_0000084] is based on the fact that negative populations typically arise from multiple firings of reactions that are only a few firings away from consuming all the molecules of one of their reactants. To focus on those reaction channels, the modified tau-leaping algorithm introduces a second control parameter nc, a positive integer that is usually set somewhere between 5 and 20. Any reaction channel with a positive propensity function that is currently within nc firings of exhausting one of its reactants is then classified as a critical reaction. The modified algorithm chooses tau in such a way that no more than one firing of all the critical reactions can occur during the leap."@en ; rdfs:subClassOf kisao:KISAO_0000252 . kisao:KISAO_0000562 a rdfs:Class ; rdfs:label "Pahle hybrid Gibson-Bruck Next Reaction method/LSODA method"@en ; rdfs:comment "Combines a deterministic numerical integration of ODEs with a stochastic simulation algorithm. The whole biochemical network is partitioned into a deterministic and a stochastic subnet internally. The deterministic subnet contains all reactions in which only species with high particle numbers take part. All reactions with at least one low-numbered species are in the stochastic subnet. The partitioning of the biochemical network can change dynamically during the simulation. The reaction probabilities of the stochastic subnet are approximated as constant during one stochastic step. The deterministic subnet is integrated with LSODA. The stochastic subnet is simulated by the Gibson-Bruck Next Reaction Method."@en ; rdfs:seeAlso , , , ; rdfs:subClassOf kisao:KISAO_0000231 . kisao:KISAO_0000436 a rdfs:Class ; rdfs:label "Dormand-Prince 8(5,3) method"@en ; rdfs:comment "This method is based on an 8(6) method by Dormand and Prince (i.e. order 8 for the integration and order 6 for error estimation) modified by Hairer and Wanner to use a 5th order error estimator with 3rd order correction."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000302 . kisao:KISAO_0000373 a rdfs:Class ; rdfs:label "differential-algebraic equation problem"@en ; rdfs:subClassOf kisao:KISAO_0000405 . kisao:KISAO_0000425 a rdfs:Class ; rdfs:label "standardising of variables"@en ; rdfs:comment "A boolean parameter of the 'hierarchical cluster-based partial least squares regression method' [http://identifiers.org/biomodels.kisao/KISAO_0000417] specifying whether the variables were standardised (divided by their standard deviations) prior to the regression analysis."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000430 . kisao:KISAO_0000510 a rdfs:Class ; rdfs:label "truncated Newton"@en ; rdfs:comment "The Truncated Newton method is a sophisticated variant of the Newton optimization method. The Newton optimization method searches for the minimum of a nonlinear function by following descent directions determined from the function's first and second partial derivatives. The Truncated Newton method does an incomplete (truncated) solution of a system of linear equations to calculate the Newton direction. This means that the actual direction chosen for the descent is between the steepest descent direction and the true Newton direction."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000471 . kisao:KISAO_0000620 a rdfs:Class ; rdfs:label "parsimonius flux balance analysis"@en ; rdfs:comment "A technique for selecting a flux distribution which is parsimonious by some metric, such as a solution which has the minimal number of active fluxes or a solution which has the smallest sum of active fluxes."@en ; rdfs:subClassOf kisao:KISAO_0000437 . kisao:KISAO_0000499 a rdfs:Class ; rdfs:label "dynamic flux balance analysis"@en ; rdfs:comment "Dynamic flux balance analysis (DFBA) enables the simulation of dynamic biological systems by assuming organisms reach steady state rapidly in response to changes in the extracellular environment. DFBA couples flux balance analysis (FBA) [http://identifiers.org/biomodels.kisao/KISAO_0000437] model approaches with dynamic model approaches."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000352 , kisao:KISAO_0000622 . kisao:KISAO_0000585 a rdfs:Class ; rdfs:label "TOMS731"@en ; rdfs:comment "Moving-grid interface for systems of one-dimensional time-dependent partial differential equations."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000369 . kisao:KISAO_0000551 a rdfs:Class ; rdfs:label "primal-dual interior point method"@en ; rdfs:comment "The Interior Point method approximates the constraints of a linear programming model as a set of boundaries surrounding a region."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000547 . kisao:KISAO_0000669 a rdfs:Class ; rdfs:label "Resource Balance Analysis"@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000630 , kisao:KISAO_0000685 . kisao:KISAO_0000800 a rdfs:Class ; rdfs:label "systems property"@en ; rdfs:comment "A systems-level property of an entire model or simulation."@en ; rdfs:subClassOf kisao:KISAO_0000831 . kisao:KISAO_0000335 a rdfs:Class ; rdfs:label "generalized stochastic simulation algorithm"@en ; rdfs:comment "Gillespie direct method [http://identifiers.org/biomodels.kisao/KISAO_0000029] follows unit-by-unit changes in the total numbers of each reactant species, it is especially well suited to the study of systems in which reactant densities are low and the application of methods based on continuum approximations, such as the traditional ordinary differential equations of chemical kinetics, is questionable. The 'generalized stochastic simulation algorithm' branch presents methods, which extend Gillespie direct method [http://identifiers.org/biomodels.kisao/KISAO_0000029] to suit to systems with other characteristics."@en ; rdfs:subClassOf kisao:KISAO_0000241 . kisao:KISAO_0000230 a rdfs:Class ; rdfs:label "minimum reactions per leap"@en ; rdfs:comment "'minimum reactions per leap' parameter is used in hybrid methods, which adaptively switch between the tau-leaping algorithm [http://identifiers.org/biomodels.kisao/KISAO_0000039] to the SSA Direct Method [http://identifiers.org/biomodels.kisao/KISAO_0000029] when the number of reactions in a single tau-leaping leap step is less than the threshold."@en ; rdfs:subClassOf kisao:KISAO_0000243 . kisao:KISAO_0000488 a rdfs:Class ; rdfs:label "seed"@en ; rdfs:comment "Random seed of a stochastic algorithm. Setting it allows one to reproduce their results while running the same algorithm on the same computer."@en ; rdfs:subClassOf kisao:KISAO_0000201 . kisao:KISAO_0000450 a rdfs:Class ; rdfs:label "asynchronous logical model simulation method"@en ; rdfs:comment "Qualitative (logical) models specify the evolution rules of their components. It the case of an asynchronous updating all enabled transitions are performed independently: a state has as many successors as the number of transitions enabled in this state. An 'asynchronous logical model simulation method' specifies a rule to guide the choice of a unique transition at each step (for example random)."@en ; rdfs:subClassOf kisao:KISAO_0000448 . kisao:KISAO_0000843 a rdfs:Class ; rdfs:label "standard error"@en ; rdfs:comment "The standard error of a set of values. If the values contain NaN the standard deviation is NaN."@en ; rdfs:subClassOf kisao:KISAO_0000824 . kisao:KISAO_0000505 a rdfs:Class ; rdfs:label "particle swarm"@en ; rdfs:comment "The particle swarm optimization method suggested by Kennedy and Eberhart is inspired by a flock of birds or a school of fish searching for food. Each particle has a position Xi and a velocity Vi in the parameter space. Additionally, it remembers its best achieved objective value O and position Mi. Dependent on its own information and the position of its best neighbor (a random subset of particles of the swarm) a new velocity is calculated. With this information the position is updated."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000472 . kisao:KISAO_0000693 a rdfs:Class ; rdfs:label "biochemical system"@en ; rdfs:subClassOf kisao:KISAO_0000690 . kisao:KISAO_0000682 a rdfs:Class ; rdfs:label "allow approximation"@en ; rdfs:comment "Whether to find an approximate solution if an exact solution could not be found."@en ; rdfs:subClassOf kisao:KISAO_0000243 . kisao:KISAO_0000540 a rdfs:Class ; rdfs:label "maximum factor to change step size by"@en ; rdfs:comment "Maximum factor to increase/decrease step size by in one step. The new step-size is chosen subject to the restriction fac1 <= current step-size / old step-size <= fac2."@en ; rdfs:subClassOf kisao:KISAO_0000242 . kisao:KISAO_0000507 a rdfs:Class ; rdfs:label "genetic algorithm SR"@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000506 . kisao:KISAO_0000613 a rdfs:Class ; rdfs:label "stochastic simulation algorithm with normally-distributed next reaction times"@en ; rdfs:subClassOf kisao:KISAO_0000335 . kisao:KISAO_0000100 a rdfs:Class ; rdfs:label "type of progression time step"@en ; rdfs:comment "Type of time steps used by the algorithm."@en ; rdfs:subClassOf kisao:KISAO_0000097 . kisao:KISAO_0000805 a rdfs:Class ; rdfs:label "elasticity coefficient (unscaled)"@en ; rdfs:comment "An unscaled elasticity coefficient of any reaction with respect to an independent element (such as a global parameter or boundary species)."@en ; rdfs:subClassOf kisao:KISAO_0000800 . kisao:KISAO_0000653 a rdfs:Class ; rdfs:label "particle number rate"@en ; rdfs:comment "Rate of a process in extensive/absolute units such as mole reactions per second."@en ; rdfs:subClassOf kisao:KISAO_0000834 . kisao:KISAO_0000347 a rdfs:Class ; rdfs:label "meshless geometry handling"@en ; rdfs:comment "Most meshless methods require a scattered set of nodal points in the domain of interest. In these methods, there may be no fixed connectivities between the nodes, unlike the finite element or finite difference methods. This feature has significant implications in modeling some physical phenomena that are characterized by a continuous change in the geometry of the domain under analysis. "@en ; rdfs:subClassOf kisao:KISAO_0000311 . kisao:KISAO_0000228 a rdfs:Class ; rdfs:label "tau-leaping epsilon"@en ; rdfs:comment "The leap condition is chosen such that the expected change in the propensity function aj(x) is bounded by Epsilon * a0 where Epsilon is an error control parameter between 0 and 1. This parameter is the basic error control mechanism for the Tau-Leaping algorithm [http://identifiers.org/biomodels.kisao/KISAO_0000039]. As Epsilon decreases the leaps become shorter and the simulation is more accurate."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000242 . kisao:KISAO_0000566 a rdfs:Class ; rdfs:label "stochastic second order Runge-Kutta method"@en ; rdfs:comment "Technique for the second order approximate numerical solution of a systems of stochastic differential equations (SDEs). The method is a generalisation of the Runge-Kutta method for ordinary differential equations to stochastic differential equations."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000564 . kisao:KISAO_0000587 a rdfs:Class ; rdfs:label "IMEX"@en ; rdfs:comment "Method for solving stiff and imaginary ODE problems"@en ; rdfs:subClassOf kisao:KISAO_0000064 . kisao:KISAO_0000420 a rdfs:Class ; rdfs:label "number of partial least squares components"@en ; rdfs:comment "Parameter used by 'partial least squares regression method' [http://identifiers.org/biomodels.kisao/KISAO_0000416] describing number of PLS components to include in the regression analysis."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000201 . kisao:KISAO_0000258 a rdfs:Class ; rdfs:label "neighbour distance"@en ; rdfs:comment "A parameter of 'Brownian diffusion Smoluchowski method' [http://identifiers.org/biomodels.kisao/KISAO_0000057]. When a surface-bound molecule diffuses off of one surface panel, it can sometimes diffuse onto the neighbouring surface tile. It does so only if the neighbouring panel is declared to be a neighbour and also the neighbour is within a distance that is set with the neighbour distance statement."@en ; rdfs:subClassOf kisao:KISAO_0000252 . kisao:KISAO_0000576 a rdfs:Class ; rdfs:label "quadratic MOMA"@en ; rdfs:comment """Minimization of metabolic adjustment (MOMA) is an extension of FBA for the prediction of flux distributions in gene knockouts. MOMA employs quadratic programming to identify the closest point (in terms of its Euclidean distance) in the permissible flux space of the knockout to the wild-type flux vector by solving the optimization problem Min sum((fluxAi - fluxBi)^2) + sum(fluxAi)^(fluxMinimizationWeight) + sum(fluxBi)^(fluxMinimizationWeight)"""@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000593 . kisao:KISAO_0000694 a rdfs:Class ; rdfs:label "ODE solver"@en ; rdfs:comment "An ODE solver is the general category of packages such as CVODE-like methods [http://identifiers.org/biomodels.kisao/KISAO_0000433] or Livermore solvers [http://identifiers.org/biomodels.kisao/KISAO_0000094] that solve systems of ordinary differential equations."@en ; rdfs:subClassOf kisao:KISAO_0000000 . kisao:KISAO_0000325 a rdfs:Class ; rdfs:label "minimum fast/discrete reaction occurrences number"@en ; rdfs:comment "Parameter of 'equation-free probabilistic steady-state approximation' method [http://identifiers.org/biomodels.kisao/KISAO_0000323], which describes the minimum number of fast/discrete reaction occurrences before their effects cause convergence to a quasi-steady-state distribution."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000242 . kisao:KISAO_0000855 a rdfs:Class ; rdfs:label "length"@en ; rdfs:comment "The number of elements of a set of values."@en ; rdfs:subClassOf kisao:KISAO_0000824 . kisao:KISAO_0000219 a rdfs:Class ; rdfs:label "maximum Adams order"@en ; rdfs:comment "This parameter is a positive integer value specifying the maximal order the non-stiff Adams integration method [http://identifiers.org/biomodels.kisao/KISAO_0000289] shall attempt before switching to the stiff BDF method [http://identifiers.org/biomodels.kisao/KISAO_0000288]."@en ; rdfs:subClassOf kisao:KISAO_0000484 . kisao:KISAO_0000554 a rdfs:Class ; rdfs:label "parsimonius flux balance analysis (minimum number of active fluxes)"@en ; rdfs:comment "A technique for selecting a parsimonious flux distribution which has a minimal number of active fluxes."@en ; rdfs:subClassOf kisao:KISAO_0000620 . kisao:KISAO_0000529 a rdfs:Class ; rdfs:label "parallelism"@en ; rdfs:comment "Number of parallel processes to use."@en ; rdfs:subClassOf kisao:KISAO_0000201 . kisao:KISAO_0000683 a rdfs:Class ; rdfs:label "relative tolerance for approximation"@en ; rdfs:comment "Relatative tolerance for an alternative approximate solution to an exact solution which could not be found."@en ; rdfs:subClassOf kisao:KISAO_0000209 . kisao:KISAO_0000555 a rdfs:Class ; rdfs:label "absolute quadrature tolerance"@en ; rdfs:comment "Absolute error tolerance of the adjoint solution."@en ; rdfs:subClassOf kisao:KISAO_0000211 . kisao:KISAO_0000624 a rdfs:Class ; rdfs:label "method for solving a system of linear equations"@en ; rdfs:comment """method for solving a system of linear equations Example system of equations: 3x + 2y - z = 0 2x - 2y + 4z = 0 -x + 1/2y - z = 0"""@en ; rdfs:subClassOf kisao:KISAO_0000000 . kisao:KISAO_0000093 a rdfs:Class ; rdfs:label "LSODPK"@en ; rdfs:comment "LSODPK is a set of FORTRAN subroutines for solving the initial value problem for stiff and nonstiff systems of ordinary differential equations. In solving stiff systems, LSODPK uses a corrector iteration composed of Newton iteration and one of four preconditioned Krylov subspace iteration methods [http://identifiers.org/biomodels.kisao/KISAO_0000354]. The user must select the desired Krylov method and supply a pair of routine to evaluate, preprocess, and solve the (left and/or right) preconditioner matrices. Aside from preconditioning, the implementation is matrix-free, meaning that explicit storage of the Jacobian (or related) matrix is not required. The method is experimental because the scope of problems for which it is effective is not well-known, and users are forewarned that LSODPK may or may not be competitive with traditional methods on a given problem. LSODPK also includes an option for a user-supplied linear system solver to be used without Krylov iteration."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000094 . kisao:KISAO_0000561 a rdfs:Class ; rdfs:label "Pahle hybrid Gibson-Bruck Next Reaction method/Runge-Kutta method"@en ; rdfs:comment "Combines a deterministic numerical integration of ODEs with a stochastic simulation algorithm. The whole biochemical network is partitioned into a deterministic and a stochastic subnet internally. The deterministic subnet contains all reactions in which only species with high particle numbers take part. All reactions with at least one low-numbered species are in the stochastic subnet. The partitioning of the biochemical network can change dynamically during the simulation. The reaction probabilities of the stochastic subnet are approximated as constant during one stochastic step. A 4th-order Runge-Kutta method is used to numerically integrate the deterministic part of the system. The stochastic subnet is simulated by the Gibson-Bruck Next Reaction Method."@en ; rdfs:seeAlso , , , ; rdfs:subClassOf kisao:KISAO_0000231 . kisao:KISAO_0000664 a rdfs:Class ; rdfs:label "Second order backward implicit product Euler scheme"@en ; rdfs:seeAlso , ; rdfs:subClassOf kisao:KISAO_0000000 . kisao:KISAO_0000297 a rdfs:Class ; rdfs:label "Lobatto method"@en ; rdfs:comment "There are three families of Lobatto methods, called IIIA, IIIB and IIIC. These are named after Rehuel Lobatto. All are implicit Runge-Kutta methods, have order 2s − 2 and they all have c1 = 0 and cs = 1."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000064 . kisao:KISAO_0000475 a rdfs:Class ; rdfs:label "integration method"@en ; rdfs:comment "the integration method used by the solver"@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000201 . kisao:KISAO_0000835 a rdfs:Class ; rdfs:label "concentration control coefficient matrix (scaled)"@en ; rdfs:comment "The scaled concentration control coefficient matrix. The dimensions are species by reactions."@en ; rdfs:subClassOf kisao:KISAO_0000800 . kisao:KISAO_0000549 a rdfs:Class ; rdfs:label "non-linear programming"@en ; rdfs:comment "Process of solving an optimization problem where some of the constraints or the objective function are nonlinear."@en ; rdfs:subClassOf kisao:KISAO_0000472 . kisao:KISAO_0000691 a rdfs:Class ; rdfs:label "metabolic system"@en ; rdfs:subClassOf kisao:KISAO_0000690 . kisao:KISAO_0000030 a rdfs:Class ; rdfs:label "Euler forward method"@en ; rdfs:comment "The Euler method is an explicit one-step method for the numerical integration of ODES with a given initial value. The calculation of the next integration step at time t+1 is based on the state of the system at time point t."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000261 . kisao:KISAO_0000209 a rdfs:Class ; rdfs:label "relative tolerance"@en ; rdfs:comment "This parameter is a numeric value specifying the desired relative tolerance the user wants to achieve. A smaller value means that the trajectory is calculated more accurately."@en ; rdfs:subClassOf kisao:KISAO_0000597 . kisao:KISAO_0000532 a rdfs:Class ; rdfs:label "loopless"@en ; rdfs:comment "Whether to return only loopless flux solutions."@en ; rdfs:subClassOf kisao:KISAO_0000201 . kisao:KISAO_0000543 a rdfs:Class ; rdfs:label "stability limit detection flag"@en ; rdfs:comment "Flag to activate stability limit detection."@en ; rdfs:subClassOf kisao:KISAO_0000242 , kisao:KISAO_0000243 . kisao:KISAO_0000453 a rdfs:Class ; rdfs:label "ordered updating policy"@en ; rdfs:comment "An updating policy that chooses a transition in a definite way."@en ; rdfs:subClassOf kisao:KISAO_0000451 . kisao:KISAO_0000045 a rdfs:Class ; rdfs:label "implicit tau-leaping method"@en ; rdfs:comment "Contrary to the explicit tau-leaping [http://identifiers.org/biomodels.kisao/KISAO_0000039 and http://identifiers.org/biomodels.kisao/KISAO_0000245 some http://identifiers.org/biomodels.kisao/KISAO_0000239] , the implicit tau-leaping allows for much larger time-steps when simulating stiff systems."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000039 . kisao:KISAO_0000647 a rdfs:Class ; rdfs:label "derivative"@en ; rdfs:comment "Rate of change of a variable with respect to another variable."@en ; rdfs:subClassOf kisao:KISAO_0000820 . kisao:KISAO_0000824 a rdfs:Class ; rdfs:label "aggregation function"@en ; rdfs:comment "A function that aggregates a set of results, reducing its dimension(s). Examples include functions that compute minima or maxima of sets of values."@en ; rdfs:subClassOf kisao:KISAO_0000633 . kisao:KISAO_0000636 a rdfs:Class ; rdfs:label "primary property"@en ; rdfs:comment "A primary output of a simulation."@en ; rdfs:subClassOf kisao:KISAO_0000820 . kisao:KISAO_0000241 a rdfs:Class ; rdfs:label "Gillespie-like method"@en ; rdfs:comment "Stochastic simulation algorithm using an approach alike the one described in Gillespie's papers of 1976 and 1977."@en ; rdfs:subClassOf kisao:KISAO_0000319 . kisao:KISAO_0000661 a rdfs:Class ; rdfs:label "logical model trap space identification method"@en ; rdfs:comment "Method for determining the trap spaces, or stable motifs or symbolic stable states, of a regulatory graph,"@en ; rdfs:subClassOf kisao:KISAO_0000658 . kisao:KISAO_0000607 a rdfs:Class ; rdfs:label "hierarchical Fehlberg method"@en ; rdfs:comment "Method for continuous simulation of hierarchically organized models, such as a model of a cellular population where each cell in the population is represented by the same species and reactions."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000086 . kisao:KISAO_0000813 a rdfs:Class ; rdfs:label "Eigenvalue matrix"@en ; rdfs:comment "The (full) eigenvalue matrix of a model. The dimensions are species by two, where the first column is the real part of the eigenvalues, and the second column is the imaginary part of the eigenvalues."@en ; rdfs:subClassOf kisao:KISAO_0000800 . kisao:KISAO_0000448 a rdfs:Class ; rdfs:label "logical model simulation method"@en ; rdfs:comment "Qualitative (logical) models specify the evolution rules of their components. In each state a number of transitions are enabled. A 'logical model simulation method' guides the choice of the transitions processed at each step."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000000 . kisao:KISAO_0000672 a rdfs:Class ; rdfs:label "Numerical Recipes in C \"quality-controlled Runge-Kutta\" method"@en ; rdfs:comment "Cash-Karp method with step size adjustment."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000321 . kisao:KISAO_0000403 a rdfs:Class ; rdfs:label "homogeneousness of equation"@en ; rdfs:comment "Homogeneous equations are of the form Ly = 0, where the differential operator L is a linear operator and y is the unknown function."@en ; rdfs:subClassOf kisao:KISAO_0000376 . kisao:KISAO_0000239 a rdfs:Class ; rdfs:label "explicit method type"@en ; rdfs:comment "Explicit methods calculate the state of a system at a later time from the state of the system at the current time. Mathematically, if Y(t) is the current system state and Y((t+delta t) is the state at the later time (delta t is a small time step), then, for an explicit method Y(t+delta t) = F(Y(t)), to find Y(t+delta t)."@en ; rdfs:subClassOf kisao:KISAO_0000238 . kisao:KISAO_0000598 a rdfs:Class ; rdfs:label "hybrid Gibson - Milstein method"@en ; rdfs:comment "A hybrid stochastic method partitions the system into subsets of fast and slow reactions and approximates the fast reactions as a continuous Markov process, using a chemical Langevin equation, and accurately describes the slow dynamics using the Gibson algorithm. Fixed time step Milstein is used for approximate numerical solution of CLE."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000352 . kisao:KISAO_0000518 a rdfs:Class ; rdfs:label "evolutionary algorithm parameter"@en ; rdfs:subClassOf kisao:KISAO_0000201 . kisao:KISAO_0000538 a rdfs:Class ; rdfs:label "safety factor on new step selection"@en ; rdfs:subClassOf kisao:KISAO_0000242 . kisao:KISAO_0000657 a rdfs:Class ; rdfs:label "sequential logical simulation method"@en ; rdfs:comment "Qualitative (logical) models specify the evolution rules of their components. In the case of a sequential updating, nodes are updated sequentially in a pre-determined deterministic order."@en ; rdfs:subClassOf kisao:KISAO_0000448 . kisao:KISAO_0000628 a rdfs:Class ; rdfs:label "modelling and simulation algorithm parameter value"@en ; rdfs:comment "A value of a parameter of an algorithm"@en . kisao:KISAO_0000679 a rdfs:Class ; rdfs:label "maximum time for approximation"@en ; rdfs:comment "Maximum amount of time to spend approximating an analysis."@en ; rdfs:subClassOf kisao:KISAO_0000681 . kisao:KISAO_0000098 a rdfs:Class ; rdfs:label "type of variable"@en ; rdfs:comment "Type of variables used for the simulation."@en ; rdfs:subClassOf kisao:KISAO_0000097 . kisao:KISAO_0000617 a rdfs:Class ; rdfs:label "IDA-CVODE hybrid method"@en ; rdfs:comment """Meta algorithm which chooses between IDA and CVODE depending on the problem to be solved. CVODE is used for ordinary differential equation (ODE) systems. IDA is used for differential-algebraic equation (DAE) systems."""@en ; rdfs:subClassOf kisao:KISAO_0000352 . kisao:KISAO_0000486 a rdfs:Class ; rdfs:label "maximum iterations"@en ; rdfs:comment "For algorithms that iterate to a solution (steady state finders in particular), a limit on the number of iterations that should be performed."@en ; rdfs:subClassOf kisao:KISAO_0000244 . kisao:KISAO_0000329 a rdfs:Class ; rdfs:label "constant-time kinetic Monte Carlo algorithm"@en ; rdfs:comment "The computational cost of the original SSA [http://identifiers.org/biomodels.kisao/KISAO_0000029] scaled linearly with the number of reactions in the network. Gibson and Bruck developed a logarithmic scaling version of the SSA which uses a priority queue or binary tree for more efficient reaction selection [http://identifiers.org/biomodels.kisao/KISAO_0000027]. More generally, this problem is one of dynamic discrete random variate generation which finds many uses in kinetic Monte Carlo and discrete event simulation. We present here a constant-time algorithm, whose cost is independent of the number of reactions, enabled by a slightly more complex underlying data structure."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000333 . kisao:KISAO_0000668 a rdfs:Class ; rdfs:label "Numerical Recipes in C \"stiff\" Rosenbrock method"@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000033 . kisao:KISAO_0000020 a rdfs:Class ; rdfs:label "PVODE"@en ; rdfs:comment "PVODE is a general-purpose solver for ordinary differential equation (ODE) systems that implements methods for both stiff and nonstiff systems. [...] In the stiff case, PVODE uses a backward differentiation formula method [http://identifiers.org/biomodels.kisao/KISAO_0000288] combined with preconditioned GMRES [http://identifiers.org/biomodels.kisao/KISAO_0000253] iteration. Parallelism is achieved by distributing the ODE solution vector into user-specified segments and parallelizing a set of vector kernels accordingly. For PDE-based ODE systems, we provide a module that generates a band block-diagonal preconditioner for use with the GMRES [http://identifiers.org/biomodels.kisao/KISAO_0000253] iteration. PVODE is based on CVODE [http://identifiers.org/biomodels.kisao/KISAO_0000019]."@en ; rdfs:seeAlso , ; rdfs:subClassOf kisao:KISAO_0000433 . kisao:KISAO_0000358 a rdfs:Class ; rdfs:label "biconjugate gradient method"@en ; rdfs:comment "The biconjugate gradient method provides a generalization of conjugate gradient method [http://identifiers.org/biomodels.kisao/KISAO_0000357] to non-symmetric matrices."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000354 . kisao:KISAO_0000550 a rdfs:Class ; rdfs:label "simplex method"@en ; rdfs:comment "Approach to solving linear programming models by hand using slack variables, tableaus, and pivot variables as a means to finding the optimal solution of an optimization problem."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000547 . kisao:KISAO_0000848 a rdfs:Class ; rdfs:label "cumulative sum ignoring NaN"@en ; rdfs:comment "The cumulative sum of a set of values, ignoring Nan entries."@en ; rdfs:subClassOf kisao:KISAO_0000824 . kisao:KISAO_0000639 a rdfs:Class ; rdfs:label "flux"@en ; rdfs:comment "A rate through an volume such as of a reaction of a constraint-based models."@en ; rdfs:subClassOf kisao:KISAO_0000831 . kisao:KISAO_0000483 a rdfs:Class ; rdfs:label "step size"@en ; rdfs:comment "the size of every step of the algorithm"@en ; rdfs:subClassOf kisao:KISAO_0000242 . kisao:KISAO_0000363 a rdfs:Class ; rdfs:label "rule-based simulation method"@en ; rdfs:comment "Rule-based models provide a powerful alternative to approaches that require explicit enumeration of all possible molecular species of a system. Such models consist of formal rules governing interactive behaviour. Rule-based simulation methods simulate such models."@en ; rdfs:subClassOf kisao:KISAO_0000000 . kisao:KISAO_0000526 a rdfs:Class ; rdfs:label "flux variability analysis"@en ; rdfs:comment "Method for determining the minimum and maximum flux of each reaction that satisfies the flux constraints of the flux balance analysis (FBA) [http://identifiers.org/biomodels.kisao/KISAO_0000437] model."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000622 , kisao:KISAO_0000630 . kisao:KISAO_0000820 a rdfs:Class ; rdfs:label "model and simulation property characteristic"@en ; rdfs:comment "A property of a variable of a model or simulation."@en . kisao:KISAO_0000437 a rdfs:Class ; rdfs:label "flux balance analysis"@en ; rdfs:comment "Flux balance analysis is a mathematical approach for analyzing the flow of metabolites through a metabolic network."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000622 , kisao:KISAO_0000630 . kisao:KISAO_0000306 a rdfs:Class ; rdfs:label "Lagrangian sliding fluid element algorithm"@en ; rdfs:comment "Because the analytic solutions to the partial differential equations require convolution integration, solutions are obtained relatively efficiently by a fast numerical method. Our approach centers on the use of a sliding fluid element algorithm for capillary convection, with the time step set equal to the length step divided by the fluid velocity. Radial fluxes by permeation between plasma, interstitial fluid, and cells and axial diffusion exchanges within each time step are calculated analytically. The method enforces mass conservation unless there is regional consumption."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000000 . kisao:KISAO_0000048 a rdfs:Class ; rdfs:label "adaptive explicit-implicit tau-leaping method"@en ; rdfs:comment "Modification of the original tau-selection strategy [http://identifiers.org/biomodels.kisao/KISAO_0000040], designed for explicit tau-leaping, is modified to apply to implicit tau-leaping, allowing for longer steps when the system is stiff. Further, an adaptive strategy is proposed that identifies stiffness and automatically chooses between the explicit and the (new) implicit tau-selection methods to achieve better efficiency."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000039 . kisao:KISAO_0000533 a rdfs:Class ; rdfs:label "pFBA factor"@en ; rdfs:comment "Maximum permissible sum of absolute fluxes."@en ; rdfs:subClassOf kisao:KISAO_0000201 . kisao:KISAO_0000364 a rdfs:Class ; rdfs:label "Adams predictor-corrector method"@en ; rdfs:comment "The combination of evaluating a single explicit integration method ('Adams-Bashforth method' [http://identifiers.org/biomodels.kisao/KISAO_0000279]) (the predictor step) in order to provide a good initial guess for the successive evaluation of an implicit method ('Adams-Moulton method' [http://identifiers.org/biomodels.kisao/KISAO_0000280]) (the corrector step) using iteration."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000289 . kisao:KISAO_0000374 a rdfs:Class ; rdfs:label "ordinary differential equation problem"@en ; rdfs:subClassOf kisao:KISAO_0000405 . kisao:KISAO_0000088 a rdfs:Class ; rdfs:label "LSODA"@en ; rdfs:comment "LSODA solves systems dy/dt = f with a dense or banded Jacobian when the problem is stiff, but it automatically selects between non-stiff (Adams [http://identifiers.org/biomodels.kisao/KISAO_0000289]) and stiff (BDF [http://identifiers.org/biomodels.kisao/KISAO_0000288]) methods. It uses the non-stiff method initially, and dynamically monitors data in order to decide which method to use."@en ; rdfs:seeAlso , , ; rdfs:subClassOf kisao:KISAO_0000094 . kisao:KISAO_0000606 a rdfs:Class ; rdfs:label "hierarchical stochastic simulation algorithm"@en ; rdfs:comment "Fast, memory-efficient method for stochastic simulation of hierarchically organized models, such as a model of a cellular population where each cell in the population is represented by the same species and reactions."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000241 . kisao:KISAO_0000108 a rdfs:Class ; rdfs:label "progression with fixed time step"@en ; rdfs:comment "Algorithm, possessing this characteristic, uses time steps of constant length to update the state of a system during the whole simulation."@en ; rdfs:subClassOf kisao:KISAO_0000100 . kisao:KISAO_0000544 a rdfs:Class ; rdfs:label "IDAS"@en ; rdfs:comment "IDAS solves real differential-algebraic systems in N-space, in the general form F(t,y,y')=0, y(t0)=y0, y'(t0)=y'0 with sensitivity analysis."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000432 . kisao:KISAO_0000314 a rdfs:Class ; rdfs:label "S-System power-law canonical differential equations solver"@en ; rdfs:comment "Ordinary differential equations can be recast into a nonlinear canonical form called an S-system. Evidence for the generality of this class comes from extensive empirical examples that have been recast and from the discovery that sets of differential equations and functions, recognized as among the most general, are special cases of S-systems. Identification of this nonlinear canonical form suggests a radically different approach to numerical solution of ordinary differential equations. By capitalizing on the regular structure of S-systems, efficient formulas for a variable-order, variable-step Taylor-series method are developed. "@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000000 . kisao:KISAO_0000803 a rdfs:Class ; rdfs:label "control coefficient (unscaled)"@en ; rdfs:comment "An unscaled control coefficient of any dependent element (such as a reaction or a floating species) with respect to an independent element (such as a global parameter or boundary species)."@en ; rdfs:subClassOf kisao:KISAO_0000800 . kisao:KISAO_0000514 a rdfs:Class ; rdfs:label "Nelder-Mead"@en ; rdfs:comment "This method also known as the simplex method is due to Nelder and Mead. A simplex is a polytope of N+1 vertices in N dimensions. The objective function is evaluated at each vertex. Dependent on these calculated values a new simplex is constructed. The simplest step is to replace the worst point with a point reflected through the centroid of the remaining N points. If this point is better than the best current point, then we can try stretching exponentially out along this line. On the other hand, if this new point isn't much better than the previous value then we are stepping across a valley, so we shrink the simplex towards the best point."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000471 . kisao:KISAO_0000234 a rdfs:Class ; rdfs:label "LSODKR"@en ; rdfs:comment "LSODKR is an initial value ODE solver for stiff and nonstiff systems. It is a variant of the LSODPK [http://identifiers.org/biomodels.kisao/KISAO_0000093] and LSODE [http://identifiers.org/biomodels.kisao/KISAO_0000071] solvers, intended mainly for large stiff systems. The main differences between LSODKR and LSODE [http://identifiers.org/biomodels.kisao/KISAO_0000071] are the following: a) for stiff systems, LSODKR uses a corrector iteration composed of Newton iteration and one of four preconditioned Krylov subspace iteration methods. The user must supply routines for the preconditioning operations, b) within the corrector iteration, LSODKR does automatic switching between functional (fixpoint) iteration and modified Newton iteration, c) LSODKR includes the ability to find roots of given functions of the solution during the integration."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000094 . kisao:KISAO_0000415 a rdfs:Class ; rdfs:label "maximum number of steps"@en ; rdfs:comment "The limit on number of internal steps before an output point."@en ; rdfs:subClassOf kisao:KISAO_0000244 . kisao:KISAO_0000618 a rdfs:Class ; rdfs:label "bunker"@en ; rdfs:comment "A variant of the stochastic simulation algorithm (SSA) in which the time to the next reaction is equated to the mean inter-event time (inverse of the sum of the propensitites of the reactions) rather than sampled from a distribution parameterized by this mean inter-event time. In this method, the next reaction time is deterministic rather than stochastic as in SSA."@en ; rdfs:subClassOf kisao:KISAO_0000335 . kisao:KISAO_0000595 a rdfs:Class ; rdfs:label "rFBA"@en ; rdfs:comment "Method for predicting metabolic fluxes under patterns of the regulation of gene expression"@en ; rdfs:subClassOf kisao:KISAO_0000352 , kisao:KISAO_0000622 . kisao:KISAO_0000341 a rdfs:Class ; rdfs:label "mixed finite element method"@en ; rdfs:comment "A 'finite element method' [http://identifiers.org/biomodels.kisao/KISAO_0000337] in which both stress and displacement fields are approximated as primary variables."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000337 . kisao:KISAO_0000027 a rdfs:Class ; rdfs:label "Gibson-Bruck next reaction algorithm"@en ; rdfs:comment "As with the first reaction method [http://identifiers.org/biomodels.kisao/KISAO_0000015], a putative reaction time is calculated for each reaction, and the reaction with the shortest reaction time will be realized. However, the unused calculated reaction times are not wasted. The set of reactions is organized in a priority queue to allow for the efficient search for the fastest reaction. In addition, by using a so-called dependency graph only those reaction times are recalculated in each step, that are dependent on the reaction, which has been realized."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000333 . kisao:KISAO_0000515 a rdfs:Class ; rdfs:label "Levenberg-Marquardt"@en ; rdfs:comment """Levenberg-Marquardt is a gradient descent method. It is a hybrid between the steepest descent and the Newton methods. Levenberg first suggested an improvement to the Newton method in order to make it more robust, i.e. to overcome the problem of non-convergence. His suggestion was to add a factor to the diagonal elements of the Hessian matrix of second derivatives when not close to the minimum (this can be judged by how positive definite the matrix is). The effect when this factor is large compared to the elements of Hessian is that the method then becomes the steepest descent method. Later Marquardt suggested that the factor should be multiplicative rather than additive and also defined a heuristic to make this factor increase or decrease. The method known as Levenberg-Marquardt is thus an adaptive method that effectively changes between the steepest descent to the Newton method."""@en ; rdfs:seeAlso , ; rdfs:subClassOf kisao:KISAO_0000471 . kisao:KISAO_0000330 a rdfs:Class ; rdfs:label "R-leaping algorithm"@en ; rdfs:comment "A novel algorithm is proposed for the acceleration of the exact stochastic simulation algorithm by a predefined number of reaction firings (R-leaping) that may occur across several reaction channels. In the present approach, the numbers of reaction firings are correlated binomial distributions and the sampling procedure is independent of any permutation of the reaction channels. This enables the algorithm to efficiently handle large systems with disparate rates, providing substantial computational savings in certain cases."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000621 . kisao:KISAO_0000838 a rdfs:Class ; rdfs:label "concentration"@en ; rdfs:comment "The intensive quantity concentration, or, the amount of the entity with respect to the entity in which it resides."@en ; rdfs:subClassOf kisao:KISAO_0000831 . kisao:KISAO_0000389 a rdfs:Class ; rdfs:label "quasi-minimal residual method"@en ; rdfs:comment "The QMR algorithm is a robust iterative solver for general nonsingular non-Hermitian linear systems. The method uses a robust implementation of the look-ahead Lanczos algorithm to generate basis vectors for the Krylov subspaces Kn(r0, A). The QMR iterates are characterized by a quasi-minimal residual property over Kn(r0, A)."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000393 . kisao:KISAO_0000286 a rdfs:Class ; rdfs:label "Euler-Maruyama method"@en ; rdfs:comment "The Euler-Maruyama method is a method for the approximate numerical solution of a stochastic differential equation, which truncates the Ito and Stratonovich Taylor series of the exact solution after the first order stochastic terms. This converges to the Ito solution with strong global order accuracy 1/2 or weak global order accuracy 1. It is a simple generalization of the Euler method [http://identifiers.org/biomodels.kisao/KISAO_0000261] for ordinary differential equations to stochastic differential equations."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000697 . kisao:KISAO_0000594 a rdfs:Class ; rdfs:label "order"@en ; rdfs:comment "Order of method"@en ; rdfs:subClassOf kisao:KISAO_0000243 . kisao:KISAO_0000309 a rdfs:Class ; rdfs:label "Crank-Nicolson method"@en ; rdfs:comment "In numerical analysis, the Crank-Nicolson method is a finite difference method [http://identifiers.org/biomodels.kisao/KISAO_0000307] used for numerically solving the heat equation and similar partial differential equations. It is a second-order method in time, implicit in time, and is numerically stable. The method was developed by John Crank and Phyllis Nicolson in the mid 20th century."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000307 . kisao:KISAO_0000844 a rdfs:Class ; rdfs:label "sum ignoring NaN"@en ; rdfs:comment "The sum of a set of values, ignoring Nan entries."@en ; rdfs:subClassOf kisao:KISAO_0000824 . kisao:KISAO_0000056 a rdfs:Class ; rdfs:label "Smoluchowski equation based method"@en ; rdfs:comment "Method based on the Smoluchowski equation."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000000 . kisao:KISAO_0000503 a rdfs:Class ; rdfs:label "simulated annealing"@en ; rdfs:comment """Simulated annealing is an optimization algorithm first proposed by Kirkpatrick et al. and was inspired by statistical mechanics and the way in which perfect crystals are formed. Perfect crystals are formed by first melting the substance of interest, and then cooling it very slowly. At large temperatures the particles vibrate with wide amplitude and this allows a search for global optimum. As the temperature decreases so do the vibrations until the system settles to the global optimum (the perfect crystal). The simulated annealing optimization algorithm uses a similar concept: the objective function is considered a measure of the energy of the system and this is maintained constant for a certain number of iterations (a temperature cycle). In each iteration, the parameters are changed to a nearby location in parameter space and the new objective function value calculated; if it decreased, then the new state is accepted, if it increased then the new state is accepted with a probability that follows a Boltzmann distribution (higher temperature means higher probability of accepting the new state). After a fixed number of iterations, the stopping criterion is checked; if it is not time to stop, then the system's temperature is reduced and the algorithm continues. Simulated annealing is a stochastic algorithm that is guaranteed to converge if ran for an infinite number of iterations. It is one of the most robust global optimization algorithms, although it is also one of the slowest. (Be warned that simulated annealing can run for hours or even days!)."""@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000472 . kisao:KISAO_0000493 a rdfs:Class ; rdfs:label "synchronous updating policy"@en ; rdfs:comment "An updating policy where all enabled transitions occur simultaneously. Thus a state will have at most one successor."@en ; rdfs:subClassOf kisao:KISAO_0000451 . kisao:KISAO_0000352 a rdfs:Class ; rdfs:label "hybrid method"@en ; rdfs:comment "A simulation methods which combines the advantages of complementary simulation approaches: the whole system is subdivided into appropriate parts and different simulation methods operate on these parts at the same time."@en ; rdfs:subClassOf kisao:KISAO_0000000 . kisao:KISAO_0000378 a rdfs:Class ; rdfs:label "implicit midpoint rule"@en ; rdfs:comment "The implicit midpoint rule is a second-order case of the more general implicit s-stage Runge-Kutta methods [http://identifiers.org/biomodels.kisao/KISAO_0000064 and (http://identifiers.org/biomodels.kisao/KISAO_0000245 some http://identifiers.org/biomodels.kisao/KISAO_0000240)]."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000064 . kisao:KISAO_0000572 a rdfs:Class ; rdfs:label "level of superimposed noise"@en ; rdfs:comment "Standard deviation of the Gaussian noise which is added to each prediction."@en ; rdfs:subClassOf kisao:KISAO_0000201 . kisao:KISAO_0000840 a rdfs:Class ; rdfs:label "minimum"@en ; rdfs:comment "The minimum of a set of values. If the values contain NaN the minimum is NaN."@en ; rdfs:subClassOf kisao:KISAO_0000824 . kisao:KISAO_0000841 a rdfs:Class ; rdfs:label "mean"@en ; rdfs:comment "The mean of a set of values. If the values contain NaN the mean is NaN."@en ; rdfs:subClassOf kisao:KISAO_0000824 . kisao:KISAO_0000806 a rdfs:Class ; rdfs:label "elasticity matrix (scaled)"@en ; rdfs:comment "The scaled elasticity matrix. The dimensions are reactions by species."@en ; rdfs:subClassOf kisao:KISAO_0000800 . kisao:KISAO_0000317 a rdfs:Class ; rdfs:label "E-Cell multi-algorithm simulation method"@en ; rdfs:comment "A modular meta-algorithm with a discrete event scheduler that can incorporate any type of time-driven simulation algorithm. It was shown that this meta-algorithm can efficiently drive simulation models with different simulation algorithms with little intrusive modification to the algorithms themselves. Only a few additional methods to handle communications between computational modules are required."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000352 . kisao:KISAO_0000817 a rdfs:Class ; rdfs:label "kernel matrix"@en ; rdfs:comment "The Kernel matrix of a model."@en ; rdfs:subClassOf kisao:KISAO_0000800 . kisao:KISAO_0000641 a rdfs:Class ; rdfs:label "bound"@en ; rdfs:comment "An upper or lower bound on an estimate of a quantity."@en ; rdfs:subClassOf kisao:KISAO_0000820 . kisao:KISAO_0000240 a rdfs:Class ; rdfs:label "implicit method type"@en ; rdfs:comment "Implicit methods find a solution by solving an equation involving both the current state of the system and the later one. Mathematically, if Y(t) is the current system state and Y((t+delta t) is the state at the later time (delta t is a small time step), then, for an implicit method one solves an equation G(Y(t), Y(t+delta t))=0, to find Y(t+delta t)."@en ; rdfs:subClassOf kisao:KISAO_0000238 . a rdfs:Class ; rdfs:comment "An unconstrained type or object"@en . kisao:KISAO_0000577 a rdfs:Class ; rdfs:label "flux minimization weight"@en ; rdfs:comment """The degree to which minimization of the sum of fluxes should be taken into account in Minimization of Metabolic Adjustment (MOMA) which solvers the optimization problem Min sum((fluxAi - fluxBi)^2) + sum(fluxAi)^(fluxMinimizationWeight) + sum(fluxBi)^(fluxMinimizationWeight)"""@en ; rdfs:subClassOf kisao:KISAO_0000201 . kisao:KISAO_0000038 a rdfs:Class ; rdfs:label "sorting stochastic simulation algorithm"@en ; rdfs:comment "In order to overcome the problem of high complexity of the stochastic simulation algorithm [http://identifiers.org/biomodels.kisao/KISAO_0000029] when simulating large systems, the sorting direct method maintains a loosely sorted order of the reactions as the simulation executes."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000333 . kisao:KISAO_0000303 a rdfs:Class ; rdfs:label "Zonneveld method"@en ; rdfs:comment "An embedded Runge-Kutta method [http://identifiers.org/biomodels.kisao/KISAO_0000302] of order 4(3), proposed by J.A. Zonneveld in 1964."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000302 . kisao:KISAO_0000583 a rdfs:Class ; rdfs:label "minimum order"@en ; rdfs:comment "Minimum order of method."@en ; rdfs:subClassOf kisao:KISAO_0000594 . kisao:KISAO_0000602 a rdfs:Class ; rdfs:label "minimum species threshold for continuous approximation"@en ; rdfs:comment "Minimum number of molecules of both reactant and product species required for approximation as a continuous Markov process."@en ; rdfs:subClassOf kisao:KISAO_0000244 . kisao:KISAO_0000201 a rdfs:Class ; rdfs:label "modelling and simulation algorithm parameter"@en ; rdfs:comment "Parameter that can be used in the simulation experiment settings."@en . kisao:KISAO_0000690 a rdfs:Class ; rdfs:label "biological system"@en ; rdfs:subClassOf kisao:KISAO_0000688 . kisao:KISAO_0000565 a rdfs:Class ; rdfs:label "absolute tolerance for root finding"@en ; rdfs:comment "Absolute error tolerance for root finding."@en ; rdfs:subClassOf kisao:KISAO_0000211 . kisao:KISAO_0000081 a rdfs:Class ; rdfs:label "estimated midpoint tau-leaping method"@en ; rdfs:comment "Estimated-Midpoint tau-Leap Method: For the selected leaping time tau which satisfies the Leap Condition, compute the expected state change lambda' = tau sumj( aj(x)vj ) during [t, t + tau). Then, with x' =x + [lambda'/2], generate for each j = 1,...,M a sample value kj of the Poisson random variable P(aj(x'), tau). Compute the actual state change, lambda = sumj( kjvj ), and effect the leap by replacing t by t + tau and x by x + lambda."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000039 . kisao:KISAO_0000336 a rdfs:Class ; rdfs:label "D-leaping method"@en ; rdfs:comment "We propose a novel, accelerated algorithm for the approximate stochastic simulation of biochemical systems with delays. The present work extends existing accelerated algorithms by distributing, in a time adaptive fashion, the delayed reactions so as to minimize the computational effort while preserving their accuracy."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000335 . kisao:KISAO_0000003 a rdfs:Class ; rdfs:label "weighted stochastic simulation algorithm"@en ; rdfs:comment "The weighted stochastic simulation algorithm manipulates the probabilities measure of biochemical systems by sampling, in order to increase the fraction of simulation runs exhibiting rare events."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000333 . kisao:KISAO_0000852 a rdfs:Class ; rdfs:label "count ignoring NaN"@en ; rdfs:comment "The number of non-zero elements of a set of values, ignoring Nan entries."@en ; rdfs:subClassOf kisao:KISAO_0000824 . kisao:KISAO_0000105 a rdfs:Class ; rdfs:label "discrete variable"@en ; rdfs:comment "Algorithm, possessing this characteristic, allows values of system's variables to change by discrete (integral) amounts."@en ; rdfs:subClassOf kisao:KISAO_0000098 . kisao:KISAO_0000599 a rdfs:Class ; rdfs:label "hybrid Gibson - Euler-Maruyama method"@en ; rdfs:comment "A hybrid stochastic method partitions the system into subsets of fast and slow reactions and approximates the fast reactions as a continuous Markov process, using a chemical Langevin equation, and accurately describes the slow dynamics using the Gibson algorithm. Fixed time step Milstein is used for approximate numerical solution of CLE."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000352 . kisao:KISAO_0000223 a rdfs:Class ; rdfs:label "number of history bins"@en ; rdfs:comment "The 'number of history bins' is only enabled for models that contain delayed or multistep reactions for specifying the granularity with which the delayed reaction solver should retain the history of species values, for species that participate in delayed reactions."@en ; rdfs:subClassOf kisao:KISAO_0000244 . kisao:KISAO_0000031 a rdfs:Class ; rdfs:label "Euler backward method"@en ; rdfs:comment "The Euler backward method is an implicit one-step method for the numerical integration of ODES with a given initial value. The next state of a system is calculated by solving an equation that considers both, the current state of the system and the later one."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000261 . kisao:KISAO_0000851 a rdfs:Class ; rdfs:label "cumulative product"@en ; rdfs:comment "The cumulative product of a set of values. If the values contain NaN the cumulative product is NaN."@en ; rdfs:subClassOf kisao:KISAO_0000824 . kisao:KISAO_0000630 a rdfs:Class ; rdfs:label "general steady state method"@en ; rdfs:comment "A method looking for a steady state of a dynamic system."@en ; rdfs:subClassOf kisao:KISAO_0000000 . kisao:KISAO_0000418 a rdfs:Class ; rdfs:label "N-way partial least squares regression method"@en ; rdfs:comment "Multivariate regression method that can be used on N-way data. Based on Partial Least Squares Regression (PLSR) [http://identifiers.org/biomodels.kisao/KISAO_0000416], which is a regression method based on estimated latent variables. PLSR is related to Principal Component Analysis (PCA) and Principal Component Regression (PCR)."@en ; rdfs:seeAlso ; rdfs:subClassOf kisao:KISAO_0000423 . kisao:KISAO_0000588 a rdfs:Class ; rdfs:label "flux sampling"@en ; rdfs:comment "Method for sampling fluxes from the null space of a flux balance analysis model"@en ; rdfs:subClassOf kisao:KISAO_0000622 , kisao:KISAO_0000630 . kisao:KISAO_0000369 a rdfs:Class ; rdfs:label "partial differential equation discretization method"@en ; rdfs:comment "A method which solves partial differential equations by discretizing them, i.e. approximating them by equations that involve a finite number of unknowns."@en ; rdfs:subClassOf kisao:KISAO_0000000 . kisao:KISAO_0000471 a rdfs:Class ; rdfs:label "local optimization algorithm"@en ; rdfs:comment "A local optimization algorithm is an optimisation algorithm [http://www.biomodels.net/kisao/KISAO#KISAO_0000470] that only finds a local optimum of a function. If several optima exist for the function, it usually depends on the starting values for the variables which optimum is found."@en ; rdfs:subClassOf kisao:KISAO_0000470 . kisao:KISAO_0000831 a rdfs:Class ; rdfs:label "model and simulation property"@en ; rdfs:comment "A variable of a model or simulation."@en . kisao:KISAO_0000255 a rdfs:Class ; rdfs:label "molecules per virtual box"@en ; rdfs:comment "Target molecules per virtual box is a parameter of 'Brownian diffusion Smoluchowski method' [http://identifiers.org/biomodels.kisao/KISAO_0000057], which sets the box sizes so that the average number of molecules per box, at simulation initiation, is close to the requested number."@en ; rdfs:subClassOf kisao:KISAO_0000260 . kisao:KISAO_0000629 a rdfs:Class ; rdfs:label "null"@en ; rdfs:subClassOf kisao:KISAO_0000628 .