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Rule-based modeling : ウィキペディア英語版
Rule-based modeling

Rule-based modeling is a modeling approach that uses a set of rules that indirectly specifies a mathematical model. The rule-set can either be translated into a model such as Markov chains or differential equations, or be treated using tools that directly work on the rule-set in place of a translated model, as the latter is typically much bigger. Rule-based modeling is especially effective in cases where the rule-set is significantly simpler than the model it implies, meaning that the model is a repeated manifestation of a limited number of patterns. An important domain where this is often the case is biochemical models of living organisms. Groups of mutually corresponding substances are subject to mutually corresponding interactions.
==For biochemical systems==

Early efforts to use rule-based modeling in simulation of biochemical systems include the stochastic simulation systems StochSim〔Morton-Firth CJ, Bray D (1998) Predicting temporal fluctuations in an intracellular signalling pathway. J Theor Biol. 1998 192(1):117-28.〕

A widely used tool for rule-based modeling of biochemical networks is BioNetGen 〔(BioNetGen )〕 It is released under the GNU GPL, version 3. BioNetGen includes a language to describe chemical substances, including the states they can assume and the bindings they can undergo. These rules can be used to create a reaction network model or to perform computer simulations directly on the rule set. The biochemical modeling framework Virtual Cell includes a BioNetGen interpreter.
A close alternative is the Kappa language.〔(Kappa )〕

抄文引用元・出典: フリー百科事典『 ウィキペディア(Wikipedia)
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