Modeling formalisms in Systems Biology
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2191-0855-1-45.pdf
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513.98 KB
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Author(s)
Machado, Daniel
Costa, Rafael S.
Rocha, Miguel
Ferreira, Eugenio C.
Tidor, Bruce
Rocha, Isabel
Date Issued
December 2011
Journal
Springer (Biomed Central Ltd.)
Publisher
Springer
Citation
Machado, Daniel et al. “Modeling Formalisms in Systems Biology.” AMB Express 1.1 (2011): 45.
Version
Author's final manuscript
Abstract
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.
MIT Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Massachusetts Institute of Technology. Department of Biological Engineering
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
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DOI of Published Version
https://doi.org/10.1186/2191-0855-1-45
