Gene filtering with optimal threshold selection

Autores
Bau Macia, Josep; Sole Casals, Jordi; Caiafa, César Federico; Lew, Sergio Eduardo
Año de publicación
2012
Idioma
inglés
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
Gene filtering is a useful preprocessing technique often applied to microarray datasets. However, it is no common practice because clear guidelines are lacking and it bears the risk of excluding some potentially relevant genes. In this work, we propose to model microarray data as a mixture of two Gaussian distributions that will allow us to obtain an optimal filter threshold in terms of the gene expression level.
Fil: Bau Macia, Josep. Universidad de Vic; España
Fil: Sole Casals, Jordi. Universidad de Vic; España
Fil: Caiafa, César Federico. Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas. Instituto Argentino de Radioastronomía. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto Argentino de Radioastronomía; Argentina
Fil: Lew, Sergio Eduardo. Universidad de Buenos Aires. Facultad de Ingeniería. Departamento de Electronica; Argentina
The Barcelona International Conference on Advances in Statistics
Barcelona
España
Universidad Autónoma de Barcelona
Materia
gene expression
gene filtering
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:11336/152252
Acceder
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network_name_str CONICET Digital (CONICET)
spelling Gene filtering with optimal threshold selectionBau Macia, JosepSole Casals, JordiCaiafa, César FedericoLew, Sergio Eduardogene expressiongene filteringhttps://purl.org/becyt/ford/1.6https://purl.org/becyt/ford/1Gene filtering is a useful preprocessing technique often applied to microarray datasets. However, it is no common practice because clear guidelines are lacking and it bears the risk of excluding some potentially relevant genes. In this work, we propose to model microarray data as a mixture of two Gaussian distributions that will allow us to obtain an optimal filter threshold in terms of the gene expression level.Fil: Bau Macia, Josep. Universidad de Vic; EspañaFil: Sole Casals, Jordi. Universidad de Vic; EspañaFil: Caiafa, César Federico. Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas. Instituto Argentino de Radioastronomía. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto Argentino de Radioastronomía; ArgentinaFil: Lew, Sergio Eduardo. Universidad de Buenos Aires. Facultad de Ingeniería. Departamento de Electronica; ArgentinaThe Barcelona International Conference on Advances in StatisticsBarcelonaEspañaUniversidad Autónoma de BarcelonaUniversidad Autónoma de Barcelona2012info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObjectCongresoBookhttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/152252Gene filtering with optimal threshold selection; The Barcelona International Conference on Advances in Statistics; Barcelona; España; 2012; 1-3CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/http://hdl.handle.net/10854/3238info:eu-repo/semantics/altIdentifier/url/http://hdl.handle.net/10854/3018Internacionalinfo:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-10-22T11:42:14Zoai:ri.conicet.gov.ar:11336/152252instacron: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:34982025-10-22 11:42:14.491CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Gene filtering with optimal threshold selection
title Gene filtering with optimal threshold selection
spellingShingle Gene filtering with optimal threshold selection
Bau Macia, Josep
gene expression
gene filtering
title_short Gene filtering with optimal threshold selection
title_full Gene filtering with optimal threshold selection
title_fullStr Gene filtering with optimal threshold selection
title_full_unstemmed Gene filtering with optimal threshold selection
title_sort Gene filtering with optimal threshold selection
dc.creator.none.fl_str_mv Bau Macia, Josep
Sole Casals, Jordi
Caiafa, César Federico
Lew, Sergio Eduardo
author Bau Macia, Josep
author_facet Bau Macia, Josep
Sole Casals, Jordi
Caiafa, César Federico
Lew, Sergio Eduardo
author_role author
author2 Sole Casals, Jordi
Caiafa, César Federico
Lew, Sergio Eduardo
author2_role author
author
author
dc.subject.none.fl_str_mv gene expression
gene filtering
topic gene expression
gene filtering
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.6
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv Gene filtering is a useful preprocessing technique often applied to microarray datasets. However, it is no common practice because clear guidelines are lacking and it bears the risk of excluding some potentially relevant genes. In this work, we propose to model microarray data as a mixture of two Gaussian distributions that will allow us to obtain an optimal filter threshold in terms of the gene expression level.
Fil: Bau Macia, Josep. Universidad de Vic; España
Fil: Sole Casals, Jordi. Universidad de Vic; España
Fil: Caiafa, César Federico. Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas. Instituto Argentino de Radioastronomía. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto Argentino de Radioastronomía; Argentina
Fil: Lew, Sergio Eduardo. Universidad de Buenos Aires. Facultad de Ingeniería. Departamento de Electronica; Argentina
The Barcelona International Conference on Advances in Statistics
Barcelona
España
Universidad Autónoma de Barcelona
description Gene filtering is a useful preprocessing technique often applied to microarray datasets. However, it is no common practice because clear guidelines are lacking and it bears the risk of excluding some potentially relevant genes. In this work, we propose to model microarray data as a mixture of two Gaussian distributions that will allow us to obtain an optimal filter threshold in terms of the gene expression level.
publishDate 2012
dc.date.none.fl_str_mv 2012
dc.type.none.fl_str_mv info:eu-repo/semantics/publishedVersion
info:eu-repo/semantics/conferenceObject
Congreso
Book
http://purl.org/coar/resource_type/c_5794
info:ar-repo/semantics/documentoDeConferencia
status_str publishedVersion
format conferenceObject
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/152252
Gene filtering with optimal threshold selection; The Barcelona International Conference on Advances in Statistics; Barcelona; España; 2012; 1-3
CONICET Digital
CONICET
url http://hdl.handle.net/11336/152252
identifier_str_mv Gene filtering with optimal threshold selection; The Barcelona International Conference on Advances in Statistics; Barcelona; España; 2012; 1-3
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://hdl.handle.net/10854/3238
info:eu-repo/semantics/altIdentifier/url/http://hdl.handle.net/10854/3018
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.coverage.none.fl_str_mv Internacional
dc.publisher.none.fl_str_mv Universidad Autónoma de Barcelona
publisher.none.fl_str_mv Universidad Autónoma de Barcelona
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 12.982451

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