Evolutionary algorithm for metabolic pathways synthesis

Metabolic pathway building is an active field of research, necessary to understand and manipulate the metabolism of organisms. There are different approaches, mainly based on classical search methods, to find linear sequences of reactions linking two compounds. However, an important limitation of th...

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Detalles Bibliográficos
Autores: Gerard, Matias Fernando, Stegmayer, Georgina, Milone, Diego Humberto
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2016
País:Argentina
Institución:Consejo Nacional de Investigaciones Científicas y Técnicas
Repositorio:CONICET Digital (CONICET)
Idioma:inglés
OAI Identifier:oai:ri.conicet.gov.ar:11336/47309
Acceso en línea:http://hdl.handle.net/11336/47309
Access Level:acceso abierto
Palabra clave:Evolutionary Algorithms
Search Strategies
De Novo Pathway Building
Reactions Network
Sets of Compounds
https://purl.org/becyt/ford/1.2
https://purl.org/becyt/ford/1
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spelling Evolutionary algorithm for metabolic pathways synthesisGerard, Matias FernandoStegmayer, GeorginaMilone, Diego HumbertoEvolutionary AlgorithmsSearch StrategiesDe Novo Pathway BuildingReactions NetworkSets of Compoundshttps://purl.org/becyt/ford/1.2https://purl.org/becyt/ford/1Metabolic pathway building is an active field of research, necessary to understand and manipulate the metabolism of organisms. There are different approaches, mainly based on classical search methods, to find linear sequences of reactions linking two compounds. However, an important limitation of these methods is the exponential increase of search trees when a large number of compounds and reactions is considered. Besides, such models do not take into account all substrates for each reaction during the search, leading to solutions that lack biological feasibility in many cases. This work proposes a new evolutionary algorithm that allows searching not only linear, but also branched metabolic pathways, formed by feasible reactions that relate multiple compounds simultaneously. Tests performed using several sets of reactions show that this algorithm is able to find feasible linear and branched metabolic pathways.Fil: Gerard, Matias Fernando. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional. Universidad Nacional del Litoral. Facultad de Ingeniería y Ciencias Hídricas. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional; ArgentinaFil: Stegmayer, Georgina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional. Universidad Nacional del Litoral. Facultad de Ingeniería y Ciencias Hídricas. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional; ArgentinaFil: Milone, Diego Humberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional. Universidad Nacional del Litoral. Facultad de Ingeniería y Ciencias Hídricas. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional; ArgentinaElsevier2016-06info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/47309Gerard, Matias Fernando; Stegmayer, Georgina; Milone, Diego Humberto; Evolutionary algorithm for metabolic pathways synthesis; Elsevier; Biosystems; 144; 6-2016; 55-670303-2647CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/http://www.sciencedirect.com/science/article/pii/S0303264716300351info:eu-repo/semantics/altIdentifier/doi/10.1016/j.biosystems.2016.04.002info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2024-05-08T13:36:37Zoai:ri.conicet.gov.ar:11336/47309instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982024-05-08 13:36:37.732CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Evolutionary algorithm for metabolic pathways synthesis
title Evolutionary algorithm for metabolic pathways synthesis
spellingShingle Evolutionary algorithm for metabolic pathways synthesis
Gerard, Matias Fernando
Evolutionary Algorithms
Search Strategies
De Novo Pathway Building
Reactions Network
Sets of Compounds
https://purl.org/becyt/ford/1.2
https://purl.org/becyt/ford/1
title_short Evolutionary algorithm for metabolic pathways synthesis
title_full Evolutionary algorithm for metabolic pathways synthesis
title_fullStr Evolutionary algorithm for metabolic pathways synthesis
title_full_unstemmed Evolutionary algorithm for metabolic pathways synthesis
title_sort Evolutionary algorithm for metabolic pathways synthesis
dc.creator.none.fl_str_mv Gerard, Matias Fernando
Stegmayer, Georgina
Milone, Diego Humberto
author Gerard, Matias Fernando
author_facet Gerard, Matias Fernando
Stegmayer, Georgina
Milone, Diego Humberto
author_role author
author2 Stegmayer, Georgina
Milone, Diego Humberto
author2_role author
author
dc.subject.none.fl_str_mv Evolutionary Algorithms
Search Strategies
De Novo Pathway Building
Reactions Network
Sets of Compounds
https://purl.org/becyt/ford/1.2
https://purl.org/becyt/ford/1
topic Evolutionary Algorithms
Search Strategies
De Novo Pathway Building
Reactions Network
Sets of Compounds
https://purl.org/becyt/ford/1.2
https://purl.org/becyt/ford/1
description Metabolic pathway building is an active field of research, necessary to understand and manipulate the metabolism of organisms. There are different approaches, mainly based on classical search methods, to find linear sequences of reactions linking two compounds. However, an important limitation of these methods is the exponential increase of search trees when a large number of compounds and reactions is considered. Besides, such models do not take into account all substrates for each reaction during the search, leading to solutions that lack biological feasibility in many cases. This work proposes a new evolutionary algorithm that allows searching not only linear, but also branched metabolic pathways, formed by feasible reactions that relate multiple compounds simultaneously. Tests performed using several sets of reactions show that this algorithm is able to find feasible linear and branched metabolic pathways.
publishDate 2016
dc.date.none.fl_str_mv 2016-06
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/47309
Gerard, Matias Fernando; Stegmayer, Georgina; Milone, Diego Humberto; Evolutionary algorithm for metabolic pathways synthesis; Elsevier; Biosystems; 144; 6-2016; 55-67
0303-2647
CONICET Digital
CONICET
url http://hdl.handle.net/11336/47309
identifier_str_mv Gerard, Matias Fernando; Stegmayer, Georgina; Milone, Diego Humberto; Evolutionary algorithm for metabolic pathways synthesis; Elsevier; Biosystems; 144; 6-2016; 55-67
0303-2647
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/http://www.sciencedirect.com/science/article/pii/S0303264716300351
info:eu-repo/semantics/altIdentifier/doi/10.1016/j.biosystems.2016.04.002
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
application/pdf
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
_version_ 1799194796454051840
score 15,811543

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