Modeling formalisms in systems biology
| Main Author: | |
|---|---|
| Publication Date: | 2011 |
| Other Authors: | , , , , |
| Format: | Article |
| Language: | eng |
| Source: | Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) |
| Download full: | https://hdl.handle.net/1822/22495 |
Summary: | 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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Modeling formalisms in systems biologySystems biologyModeling formalismsBiological networksScience & TechnologySystems 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.Research supported by grants SFRH/BD/35215/2007 and SFRH/BD/25506/2005 from the Fundacao para a Ciencia e a Tecnologia (FCT) and the MIT-Portugal Program through the project "Bridging Systems and Synthetic Biology for the development of improved microbial cell factories" (MIT-Pt/BS-BB/0082/2008).SpringerUniversidade do MinhoMachado, C. D.Costa, Rafael S.Rocha, MiguelFerreira, Eugénio C.Tidor, BruceRocha, I.20112011-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttps://hdl.handle.net/1822/22495eng2191-085510.1186/2191-0855-1-45info:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2024-05-11T07:24:25Zoai:repositorium.sdum.uminho.pt:1822/22495Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-28T16:26:06.540768Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse |
| dc.title.none.fl_str_mv |
Modeling formalisms in systems biology |
| title |
Modeling formalisms in systems biology |
| spellingShingle |
Modeling formalisms in systems biology Machado, C. D. Systems biology Modeling formalisms Biological networks Science & Technology |
| title_short |
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_sort |
Modeling formalisms in systems biology |
| author |
Machado, C. D. |
| author_facet |
Machado, C. D. Costa, Rafael S. Rocha, Miguel Ferreira, Eugénio C. Tidor, Bruce Rocha, I. |
| author_role |
author |
| author2 |
Costa, Rafael S. Rocha, Miguel Ferreira, Eugénio C. Tidor, Bruce Rocha, I. |
| author2_role |
author author author author author |
| dc.contributor.none.fl_str_mv |
Universidade do Minho |
| dc.contributor.author.fl_str_mv |
Machado, C. D. Costa, Rafael S. Rocha, Miguel Ferreira, Eugénio C. Tidor, Bruce Rocha, I. |
| dc.subject.por.fl_str_mv |
Systems biology Modeling formalisms Biological networks Science & Technology |
| topic |
Systems biology Modeling formalisms Biological networks Science & Technology |
| 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. |
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2011 |
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2011 2011-01-01T00:00:00Z |
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info:eu-repo/semantics/publishedVersion |
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info:eu-repo/semantics/article |
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article |
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https://hdl.handle.net/1822/22495 |
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https://hdl.handle.net/1822/22495 |
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eng |
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eng |
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2191-0855 10.1186/2191-0855-1-45 |
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info:eu-repo/semantics/openAccess |
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openAccess |
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application/pdf |
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Springer |
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Springer |
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