Partial Order on the set of Boolean Regulatory Functions
Autor(a) principal: | |
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Data de Publicação: | 2019 |
Outros Autores: | , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10400.7/936 |
Resumo: | Logical models have been successfully used to describe regulatory and signaling networks without requiring quantitative data. However, existing data is insufficient to adequately define a unique model, rendering the parametrization of a given model a difficult task. Here, we focus on the characterization of the set of Boolean functions compatible with a given regulatory structure, i.e. the set of all monotone nondegenerate Boolean functions. We then propose an original set of rules to locally explore the direct neighboring functions of any function in this set, without explicitly generating the whole set. Also, we provide relationships between the regulatory functions and their corresponding dynamics. Finally, we illustrate the usefulness of this approach by revisiting Probabilistic Boolean Networks with the model of T helper cell differentiation from Mendoza & Xenarios. |
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Partial Order on the set of Boolean Regulatory FunctionsBoolean regulatory networks, Boolean functions, Partial order, Discrete dynamicsLogical models have been successfully used to describe regulatory and signaling networks without requiring quantitative data. However, existing data is insufficient to adequately define a unique model, rendering the parametrization of a given model a difficult task. Here, we focus on the characterization of the set of Boolean functions compatible with a given regulatory structure, i.e. the set of all monotone nondegenerate Boolean functions. We then propose an original set of rules to locally explore the direct neighboring functions of any function in this set, without explicitly generating the whole set. Also, we provide relationships between the regulatory functions and their corresponding dynamics. Finally, we illustrate the usefulness of this approach by revisiting Probabilistic Boolean Networks with the model of T helper cell differentiation from Mendoza & Xenarios.ARCAJosé E. R. CuryPedro T. MonteiroClaudine Chaouiya2020-03-11T14:39:38Z2019-01-222019-01-22T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10400.7/936engarXiv:1901.07623 [cs.DM]info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2022-11-29T14:35:21Zoai:arca.igc.gulbenkian.pt:10400.7/936Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T16:12:08.351026Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
Partial Order on the set of Boolean Regulatory Functions |
title |
Partial Order on the set of Boolean Regulatory Functions |
spellingShingle |
Partial Order on the set of Boolean Regulatory Functions José E. R. Cury Boolean regulatory networks, Boolean functions, Partial order, Discrete dynamics |
title_short |
Partial Order on the set of Boolean Regulatory Functions |
title_full |
Partial Order on the set of Boolean Regulatory Functions |
title_fullStr |
Partial Order on the set of Boolean Regulatory Functions |
title_full_unstemmed |
Partial Order on the set of Boolean Regulatory Functions |
title_sort |
Partial Order on the set of Boolean Regulatory Functions |
author |
José E. R. Cury |
author_facet |
José E. R. Cury Pedro T. Monteiro Claudine Chaouiya |
author_role |
author |
author2 |
Pedro T. Monteiro Claudine Chaouiya |
author2_role |
author author |
dc.contributor.none.fl_str_mv |
ARCA |
dc.contributor.author.fl_str_mv |
José E. R. Cury Pedro T. Monteiro Claudine Chaouiya |
dc.subject.por.fl_str_mv |
Boolean regulatory networks, Boolean functions, Partial order, Discrete dynamics |
topic |
Boolean regulatory networks, Boolean functions, Partial order, Discrete dynamics |
description |
Logical models have been successfully used to describe regulatory and signaling networks without requiring quantitative data. However, existing data is insufficient to adequately define a unique model, rendering the parametrization of a given model a difficult task. Here, we focus on the characterization of the set of Boolean functions compatible with a given regulatory structure, i.e. the set of all monotone nondegenerate Boolean functions. We then propose an original set of rules to locally explore the direct neighboring functions of any function in this set, without explicitly generating the whole set. Also, we provide relationships between the regulatory functions and their corresponding dynamics. Finally, we illustrate the usefulness of this approach by revisiting Probabilistic Boolean Networks with the model of T helper cell differentiation from Mendoza & Xenarios. |
publishDate |
2019 |
dc.date.none.fl_str_mv |
2019-01-22 2019-01-22T00:00:00Z 2020-03-11T14:39:38Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10400.7/936 |
url |
http://hdl.handle.net/10400.7/936 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
arXiv:1901.07623 [cs.DM] |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.source.none.fl_str_mv |
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Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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RCAAP |
institution |
RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
collection |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository.name.fl_str_mv |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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