Please use this identifier to cite or link to this item: https://olympias.lib.uoi.gr/jspui/handle/123456789/7768
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dc.contributor.authorExarchos, K. P.en
dc.contributor.authorPapaloukas, C.en
dc.contributor.authorExarchos, T. P.en
dc.contributor.authorTroganis, A. N.en
dc.contributor.authorFotiadis, D. I.en
dc.date.accessioned2015-11-24T16:34:10Z-
dc.date.available2015-11-24T16:34:10Z-
dc.identifier.issn1532-0464-
dc.identifier.urihttps://olympias.lib.uoi.gr/jspui/handle/123456789/7768-
dc.rightsDefault Licence-
dc.subjectpeptide bonden
dc.subjectcis/trans isomerizationen
dc.subjectsupport vector machinesen
dc.subjectcis-trans isomerizationen
dc.subjectsecondary structure informationen
dc.subjectpeptide-bond conformationen
dc.subjectamino-acid-sequenceen
dc.subjectprotein structuresen
dc.subjectevolutionen
dc.subjectresiduesen
dc.subjectserveren
dc.titlePrediction of cis/trans isomerization using feature selection and support vector machinesen
heal.typejournalArticle-
heal.type.enJournal articleen
heal.type.elΆρθρο Περιοδικούel
heal.identifier.primaryDOI 10.1016/j.jbi.2008.05.006-
heal.identifier.secondary<Go to ISI>://000263882700015-
heal.identifier.secondaryhttp://ac.els-cdn.com/S1532046408000646/1-s2.0-S1532046408000646-main.pdf?_tid=0964545aa68ec6c50bc655b6adefb2e9&acdnat=1335944746_a94a9ac4429423cb145b6c57d1c9e566-
heal.languageen-
heal.accesscampus-
heal.recordProviderΠανεπιστήμιο Ιωαννίνων. Σχολή Επιστημών και Τεχνολογιών. Τμήμα Βιολογικών Εφαρμογών και Τεχνολογιώνel
heal.publicationDate2009-
heal.abstractIn protein structures the peptide bond is found to be in trans conformation in the majority of the cases. Only a small fraction of peptide bonds in proteins is reported to be in cis conformation. Most of these instances (>90%) occur when the peptide bond is an imide (X-Pro) rather than an amide bond (X-nonPro). Due to the implication of cis/trans isomerization in many biologically significant processes, the accurate prediction of the peptide bond conformation is of high interest. In this study, we evaluate the effect of a wide range of features, towards the reliable prediction of both proline and non-proline cis/trans isomerization. We use evolutionary profiles, secondary structure information, real-valued solvent accessibility predictions for each amino acid and the physicochemical properties of the surrounding residues. We also explore the predictive impact of a modified feature vector, which consists of condensed position-specific scoring matrices (PSSMX), secondary structure and solvent accessibility. The best discriminating ability is achieved using the first feature vector combined with a wrapper feature selection algorithm and a support vector machine (SVM). The proposed method results in 70% accuracy, 75% sensitivity and 71% positive predictive value (PPV) in the prediction of the peptide bond conformation between any two amino acids. The output of the feature selection stage is investigated in order to identify discriminatory features as well as the contribution of each neighboring residue in the formation of the peptide bond, thus, advancing our knowledge towards cis/trans isomerization. (C) 2008 Elsevier Inc. All rights reserved.en
heal.journalNameJ Biomed Informen
heal.journalTypepeer reviewed-
heal.fullTextAvailabilityTRUE-
Appears in Collections:Άρθρα σε επιστημονικά περιοδικά ( Ανοικτά)

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