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NClassG+ : A classifier for non-classically secreted Gram-positive bacterial proteins

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dc.creatorRestrepo-Montoya, Daniel
dc.creatorPino, Camilo
dc.creatorNino, Luis F
dc.creatorPatarroyo, Manuel-Elkin
dc.creatorPatarroyo, Manuel A.
dc.creator.googleRestrepo-Montoya, Danielspa
dc.creator.googlePino, Camilospa
dc.creator.googleNino, Luis Fspa
dc.creator.googlePatarroyo, Manuel Espa
dc.creator.googlePatarroyo, Manuel Aspa
dc.date.accessioned2020-05-07T13:44:02Z
dc.date.available2020-05-07T13:44:02Z
dc.date.created2011
dc.date.issued2011
dc.description.abstractBackground: Most predictive methods currently available for the identification of protein secretion mechanisms have focused on classically secreted proteins. In fact, only two methods have been reported for predicting non-classically secreted proteins of Gram-positive bacteria. This study describes the implementation of a sequence-based classifier, denoted as NClassG+, for identifying non-classically secreted Gram-positive bacterial proteins.Results: Several feature-based classifiers were trained using different sequence transformation vectors (frequencies, dipeptides, physicochemical factors and PSSM) and Support Vector Machines (SVMs) with Linear, Polynomial and Gaussian kernel functions. Nested k-fold cross-validation (CV) was applied to select the best models, using the inner CV loop to tune the model parameters and the outer CV group to compute the error. The parameters and Kernel functions and the combinations between all possible feature vectors were optimized using grid search.Conclusions: The final model was tested against an independent set not previously seen by the model, obtaining better predictive performance compared to SecretomeP V2.0 and SecretPV2.0 for the identification of non-classically secreted proteins. NClassG+ is freely available on the web at http://www.biolisi.unal.edu.co/web-servers/nclassgpositive/. © 2011 Restrepo-Montoya et al; licensee BioMed Central Ltd.eng
dc.format.mimetypeapplication/pdf
dc.identifier.doihttps://doi.org/10.1186/1471-2105-12-21
dc.identifier.issn1471-2105
dc.identifier.urihttps://repository.urosario.edu.co/handle/10336/21891
dc.language.isoengspa
dc.relation.citationTitleBMC Bioinformatics
dc.relation.citationVolumeVol. 12
dc.relation.ispartofBMC Bioinformatics, ISSN: 1471-2105 Vol. 12, (2011)spa
dc.relation.urihttps://bmcbioinformatics.biomedcentral.com/articles/10.1186/1471-2105-12-21spa
dc.rights.accesRightsinfo:eu-repo/semantics/openAccess
dc.rights.accesoAbierto (Texto Completo)spa
dc.source.instnameinstname:Universidad del Rosario
dc.source.reponamereponame:Repositorio Institucional EdocUR
dc.subject.ddcEnfermedadesspa
dc.subject.ddcMicrobiologíaspa
dc.subject.keywordSupport vector machinespa
dc.subject.keywordDipeptidespa
dc.subject.keywordMatthews correlation coefficientspa
dc.subject.keywordGaussian Kernel functionspa
dc.titleNClassG+ : A classifier for non-classically secreted Gram-positive bacterial proteinsspa
dc.typearticleeng
dc.type.hasVersioninfo:eu-repo/semantics/publishedVersion
dc.type.spaArtículospa
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