Modeling formalisms in Systems Biology
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...
| Main Authors: | , , , , , |
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| Other Authors: | |
| Format: | Article |
| Language: | English |
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Springer
2012
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| Online Access: | http://hdl.handle.net/1721.1/69812 https://orcid.org/0000-0002-3320-3969 |
| _version_ | 1826199457105969152 |
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| author | Machado, Daniel Costa, Rafael S. Rocha, Miguel Ferreira, Eugenio C. Tidor, Bruce Rocha, Isabel |
| author2 | Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory |
| author_facet | Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory Machado, Daniel Costa, Rafael S. Rocha, Miguel Ferreira, Eugenio C. Tidor, Bruce Rocha, Isabel |
| author_sort | Machado, Daniel |
| collection | MIT |
| description | 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. |
| first_indexed | 2024-09-23T11:20:12Z |
| format | Article |
| id | mit-1721.1/69812 |
| institution | Massachusetts Institute of Technology |
| language | English |
| last_indexed | 2024-09-23T11:20:12Z |
| publishDate | 2012 |
| publisher | Springer |
| record_format | dspace |
| spelling | mit-1721.1/698122022-09-27T18:49:20Z Modeling formalisms in Systems Biology Machado, Daniel Costa, Rafael S. Rocha, Miguel Ferreira, Eugenio C. Tidor, Bruce Rocha, Isabel 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 Tidor, Bruce 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. Fundação para a Ciência e a Tecnologia (SFRH/BD/35215/2007) Fundação para a Ciência e a Tecnologia (SFRH/BD/25506/2005) MIT-Portugal Program (project "Bridging Systems and Synthetic Biology for the development of improved microbial cell factories" (MIT-Pt/BS-BB/0082/2008)) 2012-03-16T16:15:49Z 2012-03-16T16:15:49Z 2011-12 2011-11 2012-02-23T16:06:12Z Article http://purl.org/eprint/type/JournalArticle 2191-0855 http://hdl.handle.net/1721.1/69812 Machado, Daniel et al. “Modeling Formalisms in Systems Biology.” AMB Express 1.1 (2011): 45. https://orcid.org/0000-0002-3320-3969 en http://dx.doi.org/10.1186/2191-0855-1-45 Springer (Biomed Central Ltd.) http://creativecommons.org/licenses/by/2.0 Machado et al.; licensee BioMed Central Ltd. application/pdf Springer |
| spellingShingle | Machado, Daniel Costa, Rafael S. Rocha, Miguel Ferreira, Eugenio C. Tidor, Bruce Rocha, Isabel Modeling formalisms in Systems Biology |
| title | Modeling formalisms in Systems Biology |
| title_full | Modeling formalisms in Systems Biology |
| title_fullStr | Modeling formalisms in Systems Biology |
| title_full_unstemmed | Modeling formalisms in Systems Biology |
| title_short | Modeling formalisms in Systems Biology |
| title_sort | modeling formalisms in systems biology |
| url | http://hdl.handle.net/1721.1/69812 https://orcid.org/0000-0002-3320-3969 |
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