Modeling formalisms in Systems BiologyReport as inadecuate

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AMB Express

, 1:45

First Online: 05 December 2011Received: 18 November 2011Accepted: 05 December 2011


Systems Biology has taken advantage of computational tools and high-throughput experimental data to model several biological processes. These include signaling, gene regulatory, and metabolic networks. However, most of these models are specific to each kind of network. Their interconnection demands a whole-cell modeling framework for a complete understanding of cellular systems. We describe the features required by an integrated framework for modeling, analyzing and simulating biological processes, and review several modeling formalisms that have been used in Systems Biology including Boolean networks, Bayesian networks, Petri nets, process algebras, constraint-based models, differential equations, rule-based models, interacting state machines, cellular automata, and agent-based models. We compare the features provided by different formalisms, and discuss recent approaches in the integration of these formalisms, as well as possible directions for the future.

KeywordsSystems Biology Modeling Formalisms Biological Networks Electronic supplementary materialThe online version of this article doi:10.1186-2191-0855-1-45 contains supplementary material, which is available to authorized users.

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Author: Daniel Machado - Rafael S Costa - Miguel Rocha - Eugénio C Ferreira - Bruce Tidor - Isabel Rocha


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