QSLiM Finder: Improved short linear motif prediction using specific query protein data

Autores
Palopoli, Nicolás; Lythgow, Kieren T.; Edwards, Richard J.
Año de publicación
2015
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Motivation: The sensitivity of de novo short linear motif (SLiM) prediction is limited by the number of patterns (the motif space) being assessed for enrichment. QSLiMFinder uses specific query protein information to restrict the motif space and thereby increase the sensitivity and specificity of predictions. Results: QSLiMFinder was extensively benchmarked using known SLiM-containing proteins and simulated protein interaction datasets of real human proteins. Exploiting prior knowledge of a query protein likely to be involved in a SLiM-mediated interaction increased the proportion of true positives correctly returned and reduced the proportion of datasets returning a false positive prediction. The biggest improvement was seen if a short region of the query protein flanking the interaction site was known.
Fil: Palopoli, Nicolás. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. University of Southampton; Reino Unido
Fil: Lythgow, Kieren T.. University of Southampton; Reino Unido. Public Health England; Reino Unido
Fil: Edwards, Richard J.. University of New South Wales; Australia. University of Southampton; Reino Unido
Materia
PROTEIN-PROTEIN INTERACTION
SHORT LINEAR MOTIF
SLIM
BENCHMARK
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:11336/98772

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network_name_str CONICET Digital (CONICET)
spelling QSLiM Finder: Improved short linear motif prediction using specific query protein dataPalopoli, NicolásLythgow, Kieren T.Edwards, Richard J.PROTEIN-PROTEIN INTERACTIONSHORT LINEAR MOTIFSLIMBENCHMARKhttps://purl.org/becyt/ford/1.2https://purl.org/becyt/ford/1Motivation: The sensitivity of de novo short linear motif (SLiM) prediction is limited by the number of patterns (the motif space) being assessed for enrichment. QSLiMFinder uses specific query protein information to restrict the motif space and thereby increase the sensitivity and specificity of predictions. Results: QSLiMFinder was extensively benchmarked using known SLiM-containing proteins and simulated protein interaction datasets of real human proteins. Exploiting prior knowledge of a query protein likely to be involved in a SLiM-mediated interaction increased the proportion of true positives correctly returned and reduced the proportion of datasets returning a false positive prediction. The biggest improvement was seen if a short region of the query protein flanking the interaction site was known.Fil: Palopoli, Nicolás. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. University of Southampton; Reino UnidoFil: Lythgow, Kieren T.. University of Southampton; Reino Unido. Public Health England; Reino UnidoFil: Edwards, Richard J.. University of New South Wales; Australia. University of Southampton; Reino UnidoOxford University Press2015-03info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/98772Palopoli, Nicolás; Lythgow, Kieren T.; Edwards, Richard J.; QSLiM Finder: Improved short linear motif prediction using specific query protein data; Oxford University Press; Bioinformatics (Oxford, England); 31; 14; 3-2015; 2284-22931367-4803CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/http://bioinformatics.oxfordjournals.org/content/early/2015/04/03/bioinformatics.btv155info:eu-repo/semantics/altIdentifier/doi/10.1093/bioinformatics/btv155info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-03T09:44:50Zoai:ri.conicet.gov.ar:11336/98772instacron: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:34982025-09-03 09:44:51.099CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv QSLiM Finder: Improved short linear motif prediction using specific query protein data
title QSLiM Finder: Improved short linear motif prediction using specific query protein data
spellingShingle QSLiM Finder: Improved short linear motif prediction using specific query protein data
Palopoli, Nicolás
PROTEIN-PROTEIN INTERACTION
SHORT LINEAR MOTIF
SLIM
BENCHMARK
title_short QSLiM Finder: Improved short linear motif prediction using specific query protein data
title_full QSLiM Finder: Improved short linear motif prediction using specific query protein data
title_fullStr QSLiM Finder: Improved short linear motif prediction using specific query protein data
title_full_unstemmed QSLiM Finder: Improved short linear motif prediction using specific query protein data
title_sort QSLiM Finder: Improved short linear motif prediction using specific query protein data
dc.creator.none.fl_str_mv Palopoli, Nicolás
Lythgow, Kieren T.
Edwards, Richard J.
author Palopoli, Nicolás
author_facet Palopoli, Nicolás
Lythgow, Kieren T.
Edwards, Richard J.
author_role author
author2 Lythgow, Kieren T.
Edwards, Richard J.
author2_role author
author
dc.subject.none.fl_str_mv PROTEIN-PROTEIN INTERACTION
SHORT LINEAR MOTIF
SLIM
BENCHMARK
topic PROTEIN-PROTEIN INTERACTION
SHORT LINEAR MOTIF
SLIM
BENCHMARK
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.2
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv Motivation: The sensitivity of de novo short linear motif (SLiM) prediction is limited by the number of patterns (the motif space) being assessed for enrichment. QSLiMFinder uses specific query protein information to restrict the motif space and thereby increase the sensitivity and specificity of predictions. Results: QSLiMFinder was extensively benchmarked using known SLiM-containing proteins and simulated protein interaction datasets of real human proteins. Exploiting prior knowledge of a query protein likely to be involved in a SLiM-mediated interaction increased the proportion of true positives correctly returned and reduced the proportion of datasets returning a false positive prediction. The biggest improvement was seen if a short region of the query protein flanking the interaction site was known.
Fil: Palopoli, Nicolás. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. University of Southampton; Reino Unido
Fil: Lythgow, Kieren T.. University of Southampton; Reino Unido. Public Health England; Reino Unido
Fil: Edwards, Richard J.. University of New South Wales; Australia. University of Southampton; Reino Unido
description Motivation: The sensitivity of de novo short linear motif (SLiM) prediction is limited by the number of patterns (the motif space) being assessed for enrichment. QSLiMFinder uses specific query protein information to restrict the motif space and thereby increase the sensitivity and specificity of predictions. Results: QSLiMFinder was extensively benchmarked using known SLiM-containing proteins and simulated protein interaction datasets of real human proteins. Exploiting prior knowledge of a query protein likely to be involved in a SLiM-mediated interaction increased the proportion of true positives correctly returned and reduced the proportion of datasets returning a false positive prediction. The biggest improvement was seen if a short region of the query protein flanking the interaction site was known.
publishDate 2015
dc.date.none.fl_str_mv 2015-03
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/11336/98772
Palopoli, Nicolás; Lythgow, Kieren T.; Edwards, Richard J.; QSLiM Finder: Improved short linear motif prediction using specific query protein data; Oxford University Press; Bioinformatics (Oxford, England); 31; 14; 3-2015; 2284-2293
1367-4803
CONICET Digital
CONICET
url http://hdl.handle.net/11336/98772
identifier_str_mv Palopoli, Nicolás; Lythgow, Kieren T.; Edwards, Richard J.; QSLiM Finder: Improved short linear motif prediction using specific query protein data; Oxford University Press; Bioinformatics (Oxford, England); 31; 14; 3-2015; 2284-2293
1367-4803
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://bioinformatics.oxfordjournals.org/content/early/2015/04/03/bioinformatics.btv155
info:eu-repo/semantics/altIdentifier/doi/10.1093/bioinformatics/btv155
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 Oxford University Press
publisher.none.fl_str_mv Oxford University Press
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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