On Evolutionary Algorithms for Biclustering of Gene Expression Data

Autores
Carballido, Jessica Andrea; Gallo, Cristian Andrés; Dussaut, Julieta Sol; Ponzoni, Ignacio
Año de publicación
2015
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Past decades have seen the rapid development of microarray technologies making available large amounts of gene expression data. Hence, has become increasingly important to count with reliable methods that interpret this information in order to discover new biological knowledge. In this review paper we aim to describe the main existing evolutionary methods that analyze microarray gene expression data by means of biclustering techniques. Strategies will be classified according to the evaluation metric they use to quantify the quality of the biclusters. In this context, the main evaluation measures namely mean squared residue, virtual error and transposed virtual error are first presented. Then, the main evolutionary algorithms, which find biclusters in gene expression data matrices using those metrics, are described and compared.
Fil: Carballido, Jessica Andrea. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional del Sur. Departamento de Ciencias e Ingeniería de la Computación; Argentina
Fil: Gallo, Cristian Andrés. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca; Argentina. Universidad Nacional del Sur. Departamento de Ciencias e Ingeniería de la Computación; Argentina
Fil: Dussaut, Julieta Sol. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional del Sur. Departamento de Ciencias e Ingeniería de la Computación; Argentina
Fil: Ponzoni, Ignacio. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional del Sur. Departamento de Ciencias e Ingeniería de la Computación; Argentina
Materia
Evolutionary Algorithms
Biclustering
Gene Expression Data
Evaluation Metrics
Microarray Analysis
Regulatory Networks
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/45891
Acceder
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network_name_str CONICET Digital (CONICET)
spelling On Evolutionary Algorithms for Biclustering of Gene Expression DataCarballido, Jessica AndreaGallo, Cristian AndrésDussaut, Julieta SolPonzoni, IgnacioEvolutionary AlgorithmsBiclusteringGene Expression DataEvaluation MetricsMicroarray AnalysisRegulatory Networkshttps://purl.org/becyt/ford/1.2https://purl.org/becyt/ford/1Past decades have seen the rapid development of microarray technologies making available large amounts of gene expression data. Hence, has become increasingly important to count with reliable methods that interpret this information in order to discover new biological knowledge. In this review paper we aim to describe the main existing evolutionary methods that analyze microarray gene expression data by means of biclustering techniques. Strategies will be classified according to the evaluation metric they use to quantify the quality of the biclusters. In this context, the main evaluation measures namely mean squared residue, virtual error and transposed virtual error are first presented. Then, the main evolutionary algorithms, which find biclusters in gene expression data matrices using those metrics, are described and compared.Fil: Carballido, Jessica Andrea. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional del Sur. Departamento de Ciencias e Ingeniería de la Computación; ArgentinaFil: Gallo, Cristian Andrés. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca; Argentina. Universidad Nacional del Sur. Departamento de Ciencias e Ingeniería de la Computación; ArgentinaFil: Dussaut, Julieta Sol. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional del Sur. Departamento de Ciencias e Ingeniería de la Computación; ArgentinaFil: Ponzoni, Ignacio. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional del Sur. Departamento de Ciencias e Ingeniería de la Computación; ArgentinaBentham Science Publishers2015-07info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/45891Carballido, Jessica Andrea; Gallo, Cristian Andrés; Dussaut, Julieta Sol; Ponzoni, Ignacio; On Evolutionary Algorithms for Biclustering of Gene Expression Data; Bentham Science Publishers; Current Bioinformatics; 10; 3; 7-2015; 259-2671574-8936CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/doi/10.2174/1574893609666140829204739info:eu-repo/semantics/altIdentifier/url/http://www.eurekaselect.com/124284/articleinfo:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-10-15T15:39:00Zoai:ri.conicet.gov.ar:11336/45891instacron: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:34982025-10-15 15:39:01.086CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv On Evolutionary Algorithms for Biclustering of Gene Expression Data
title On Evolutionary Algorithms for Biclustering of Gene Expression Data
spellingShingle On Evolutionary Algorithms for Biclustering of Gene Expression Data
Carballido, Jessica Andrea
Evolutionary Algorithms
Biclustering
Gene Expression Data
Evaluation Metrics
Microarray Analysis
Regulatory Networks
title_short On Evolutionary Algorithms for Biclustering of Gene Expression Data
title_full On Evolutionary Algorithms for Biclustering of Gene Expression Data
title_fullStr On Evolutionary Algorithms for Biclustering of Gene Expression Data
title_full_unstemmed On Evolutionary Algorithms for Biclustering of Gene Expression Data
title_sort On Evolutionary Algorithms for Biclustering of Gene Expression Data
dc.creator.none.fl_str_mv Carballido, Jessica Andrea
Gallo, Cristian Andrés
Dussaut, Julieta Sol
Ponzoni, Ignacio
author Carballido, Jessica Andrea
author_facet Carballido, Jessica Andrea
Gallo, Cristian Andrés
Dussaut, Julieta Sol
Ponzoni, Ignacio
author_role author
author2 Gallo, Cristian Andrés
Dussaut, Julieta Sol
Ponzoni, Ignacio
author2_role author
author
author
dc.subject.none.fl_str_mv Evolutionary Algorithms
Biclustering
Gene Expression Data
Evaluation Metrics
Microarray Analysis
Regulatory Networks
topic Evolutionary Algorithms
Biclustering
Gene Expression Data
Evaluation Metrics
Microarray Analysis
Regulatory Networks
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.2
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv Past decades have seen the rapid development of microarray technologies making available large amounts of gene expression data. Hence, has become increasingly important to count with reliable methods that interpret this information in order to discover new biological knowledge. In this review paper we aim to describe the main existing evolutionary methods that analyze microarray gene expression data by means of biclustering techniques. Strategies will be classified according to the evaluation metric they use to quantify the quality of the biclusters. In this context, the main evaluation measures namely mean squared residue, virtual error and transposed virtual error are first presented. Then, the main evolutionary algorithms, which find biclusters in gene expression data matrices using those metrics, are described and compared.
Fil: Carballido, Jessica Andrea. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional del Sur. Departamento de Ciencias e Ingeniería de la Computación; Argentina
Fil: Gallo, Cristian Andrés. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca; Argentina. Universidad Nacional del Sur. Departamento de Ciencias e Ingeniería de la Computación; Argentina
Fil: Dussaut, Julieta Sol. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional del Sur. Departamento de Ciencias e Ingeniería de la Computación; Argentina
Fil: Ponzoni, Ignacio. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional del Sur. Departamento de Ciencias e Ingeniería de la Computación; Argentina
description Past decades have seen the rapid development of microarray technologies making available large amounts of gene expression data. Hence, has become increasingly important to count with reliable methods that interpret this information in order to discover new biological knowledge. In this review paper we aim to describe the main existing evolutionary methods that analyze microarray gene expression data by means of biclustering techniques. Strategies will be classified according to the evaluation metric they use to quantify the quality of the biclusters. In this context, the main evaluation measures namely mean squared residue, virtual error and transposed virtual error are first presented. Then, the main evolutionary algorithms, which find biclusters in gene expression data matrices using those metrics, are described and compared.
publishDate 2015
dc.date.none.fl_str_mv 2015-07
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/11336/45891
Carballido, Jessica Andrea; Gallo, Cristian Andrés; Dussaut, Julieta Sol; Ponzoni, Ignacio; On Evolutionary Algorithms for Biclustering of Gene Expression Data; Bentham Science Publishers; Current Bioinformatics; 10; 3; 7-2015; 259-267
1574-8936
CONICET Digital
CONICET
url http://hdl.handle.net/11336/45891
identifier_str_mv Carballido, Jessica Andrea; Gallo, Cristian Andrés; Dussaut, Julieta Sol; Ponzoni, Ignacio; On Evolutionary Algorithms for Biclustering of Gene Expression Data; Bentham Science Publishers; Current Bioinformatics; 10; 3; 7-2015; 259-267
1574-8936
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.2174/1574893609666140829204739
info:eu-repo/semantics/altIdentifier/url/http://www.eurekaselect.com/124284/article
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
dc.publisher.none.fl_str_mv Bentham Science Publishers
publisher.none.fl_str_mv Bentham Science Publishers
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
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
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score 13.22299

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