Modeling formalisms in Systems Biology
Open accessAbstract
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.
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There is more third party support for SBML and it is semantically richer compared to CellML.
“There is more third party support for SBML and it is a semantically richer language compared to CellML [13, 28].”
From Adapting modeling and simulation credibility standards to computational systems biology (2023) · cites this paper as [13]
The Standardization section (page unavailable) calls SBML the de facto standard and says more than 200 tools support it; the Perspective section also calls it the most popular standard. This supports the claim about third-party support, but the paper does not say SBML is semantically richer than CellML. It describes CellML as having a similar purpose but being more generic. (LLM, conf=0.86)
Experimental — accuracy not yet measuredSBML is the most widely used model format and the de facto language for systems biology models.
“The most widely used model format is SBML (Systems Biology Markup Language) [10, 13, 17, 18].”
From Adapting modeling and simulation credibility standards to computational systems biology (2023) · cites this paper as [13]
Systems biology model representation has become standardized using XML-based languages SBML, CellML, and BioPAX.
“For this reason, systems biology model representation has become standardized using XML-based languages SBML [10, 13], CellML [14], and BioPAX [15].”
From Adapting modeling and simulation credibility standards to computational systems biology (2023) · cites this paper as [13]
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References 218 · Cited by 189
Research works printed but not linked: 3
- Gomperts B Kramer I Tatham P Signal transduction 2009 Academic Press
- Lee J Gianchandani E Eddy J Papin J Dynamic analysis of integrated signaling, metabolic, and regulatory networks PLoS Comput Biol 2008 4 5 e1000086 PMC2377155 18483615
- Regev A Silverman W Shapiro E Representing biomolecular processes with computer process algebra: π-calculus programs of signal transduction pathways Proceedings of Pacific Symposium of Biocomputing 2000 World Scientific Press, Singapore
- Authors
- Machado, D., Costa, R. S., Rocha, M., Ferreira, E. C., Tidor, B., & Rocha, I.
- Affiliations
- Institute for Biotechnology and Bioengineering (PT)
- University of Minho (PT)
- Massachusetts Institute of Technology (US)
- Corresponding author
- Machado, Daniel
- Venue
- AMB Express
- Published
- 2011
- Volume
- 1
- Issue
- 1
- Pages
- 45
- ISSN
- 2191-0855 (ISSN-L)
- PMC
- PMC3285092
- OpenAlex
- W2154601808
- Cited by
- 189
- References
- 218
- Citations by year
- 2026: 5 · 2025: 6 · 2024: 8 · 2023: 6 · 2022: 17 · 2021: 8 · 2020: 13 · 2019: 11 · 2018: 16 · 2017: 12 · 2016: 24 · 2015: 22 · 2014: 15 · 2013: 19 · 2012: 6
- FWCI
- 5.33
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- AMB Express (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DSpace@MIT (Massachusetts Institute of Technology) (submittedVersion, cc-by-nc-sa)
- Portuguese National Funding Agency for Science, Research and Technology (RCAAP Project by FCT) (submittedVersion, other-oa)
- Funders
- Massachusetts Institute of Technology
- Universidade do Minho
- Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology
- Fundação para a Ciência e a Tecnologia (SFRH/BD/35215/2007)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene Regulatory Network Analysis
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Microbial Metabolic Engineering and Bioproduction
- Keywords
- whole-cell modeling, Boolean networks, Bayesian networks, Petri nets, process algebra, constraint-based modeling, differential equations, rule-based models, cellular automata, agent-based modeling, model integration, signaling networks, gene regulatory networks, metabolic networks
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