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dc.contributor.authorKönig, Caroline
dc.contributor.authorAlquézar Mancho, René
dc.contributor.authorVellido Alcacena, Alfredo
dc.contributor.authorGiraldo Arjonilla, Jesús
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament de Ciències de la Computació
dc.date.accessioned2015-06-19T08:03:26Z
dc.date.available2015-06-19T08:03:26Z
dc.date.created2014-10-23
dc.date.issued2014-10-23
dc.identifier.citationKönig, C. [et al.]. Reducing the n-gram feature space of class C GPCRs to subtype-discriminating patterns. "Journal of integrative bioinformatics", 23 Octubre 2014, vol. 11, núm. 3.
dc.identifier.issn1613-4516
dc.identifier.urihttp://hdl.handle.net/2117/28347
dc.description.abstractG protein-coupled receptors (GPCRs) are a large and heterogeneous superfamily of receptors that are key cell players for their role as extracellular signal transmitters. Class C GPCRs, in particular, are of great interest in pharmacology. The lack of knowledge about their full 3-D structure prompts the use of their primary amino acid sequences for the construction of robust classifiers, capable of discriminating their different subtypes. In this paper, we investigate the use of feature selection techniques to build Support Vector Machine (SVM)-based classification models from selected receptor subsequences described as n-grams. We show that this approach to classification is useful for finding class C GPCR subtype-specific motifs.
dc.format.extent17 p.
dc.language.isoeng
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 Spain
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subjectÀrees temàtiques de la UPC::Informàtica::Intel·ligència artificial
dc.subjectÀrees temàtiques de la UPC::Informàtica::Aplicacions de la informàtica::Bioinformàtica
dc.subject.lcshProtein research
dc.subject.otherG protein-coupled receptors
dc.subject.otherGPCRs
dc.subject.otherSupport vector machine-based classification
dc.subject.otherSVM-based classification
dc.titleReducing the n-gram feature space of class C GPCRs to subtype-discriminating patterns
dc.typeArticle
dc.subject.lemacProteïnes -- Investigació
dc.contributor.groupUniversitat Politècnica de Catalunya. VIS - Visió Artificial i Sistemes Intel.ligents
dc.contributor.groupUniversitat Politècnica de Catalunya. SOCO - Soft Computing
dc.identifier.doi10.2390/biecoll-jib-2014-254
dc.description.peerreviewedPeer Reviewed
dc.relation.publisherversionhttp://journal.imbio.de/article.php?aid=254
dc.rights.accessOpen Access
drac.iddocument16495527
dc.description.versionPostprint (published version)
upcommons.citation.authorKönig, C.; Alquezar, R.; Vellido, A.; Giraldo, J.
upcommons.citation.publishedtrue
upcommons.citation.publicationNameJournal of integrative bioinformatics
upcommons.citation.volume11
upcommons.citation.number3
upcommons.citation.startingPagePaper 254


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