Assessment of protein disorder region predictions in CASP10

Handle URI:
http://hdl.handle.net/10754/597613
Title:
Assessment of protein disorder region predictions in CASP10
Authors:
Monastyrskyy, Bohdan; Kryshtafovych, Andriy; Moult, John; Tramontano, Anna; Fidelis, Krzysztof
Abstract:
The article presents the assessment of disorder region predictions submitted to CASP10. The evaluation is based on the three measures tested in previous CASPs: (i) balanced accuracy, (ii) the Matthews correlation coefficient for the binary predictions, and (iii) the area under the curve in the receiver operating characteristic (ROC) analysis of predictions using probability annotation. We also performed new analyses such as comparison of the submitted predictions with those obtained with a Naïve disorder prediction method and with predictions from the disorder prediction databases D2P2 and MobiDB. On average, the methods participating in CASP10 demonstrated slightly better performance than those in CASP9.
Citation:
Monastyrskyy B, Kryshtafovych A, Moult J, Tramontano A, Fidelis K (2013) Assessment of protein disorder region predictions in CASP10. Proteins: Structure, Function, and Bioinformatics 82: 127–137. Available: http://dx.doi.org/10.1002/prot.24391.
Publisher:
Wiley-Blackwell
Journal:
Proteins: Structure, Function, and Bioinformatics
KAUST Grant Number:
KUK-I1–012-43
Issue Date:
22-Nov-2013
DOI:
10.1002/prot.24391
PubMed ID:
23946100
PubMed Central ID:
PMC4406047
Type:
Article
ISSN:
0887-3585
Sponsors:
Grant sponsor: NIGMS/NIH; Grant number: R01GM100482 (to KF); Grant sponsor:King Abdullah University of Science and Technology (KAUST); Grant number:Award No. KUK-I1–012-43 (to AT); Grant sponsor: EMBO.
Appears in Collections:
Publications Acknowledging KAUST Support

Full metadata record

DC FieldValue Language
dc.contributor.authorMonastyrskyy, Bohdanen
dc.contributor.authorKryshtafovych, Andriyen
dc.contributor.authorMoult, Johnen
dc.contributor.authorTramontano, Annaen
dc.contributor.authorFidelis, Krzysztofen
dc.date.accessioned2016-02-25T12:43:04Zen
dc.date.available2016-02-25T12:43:04Zen
dc.date.issued2013-11-22en
dc.identifier.citationMonastyrskyy B, Kryshtafovych A, Moult J, Tramontano A, Fidelis K (2013) Assessment of protein disorder region predictions in CASP10. Proteins: Structure, Function, and Bioinformatics 82: 127–137. Available: http://dx.doi.org/10.1002/prot.24391.en
dc.identifier.issn0887-3585en
dc.identifier.pmid23946100en
dc.identifier.doi10.1002/prot.24391en
dc.identifier.urihttp://hdl.handle.net/10754/597613en
dc.description.abstractThe article presents the assessment of disorder region predictions submitted to CASP10. The evaluation is based on the three measures tested in previous CASPs: (i) balanced accuracy, (ii) the Matthews correlation coefficient for the binary predictions, and (iii) the area under the curve in the receiver operating characteristic (ROC) analysis of predictions using probability annotation. We also performed new analyses such as comparison of the submitted predictions with those obtained with a Naïve disorder prediction method and with predictions from the disorder prediction databases D2P2 and MobiDB. On average, the methods participating in CASP10 demonstrated slightly better performance than those in CASP9.en
dc.description.sponsorshipGrant sponsor: NIGMS/NIH; Grant number: R01GM100482 (to KF); Grant sponsor:King Abdullah University of Science and Technology (KAUST); Grant number:Award No. KUK-I1–012-43 (to AT); Grant sponsor: EMBO.en
dc.publisherWiley-Blackwellen
dc.subjectIntrinsically Disordered Proteinsen
dc.subjectCaspen
dc.subjectAssessment Of Disorder Predictionen
dc.subjectUnstructured Proteinsen
dc.subjectPrediction Of Disordered Regionsen
dc.subject.meshProtein Conformationen
dc.subject.meshModels, Molecularen
dc.titleAssessment of protein disorder region predictions in CASP10en
dc.typeArticleen
dc.identifier.journalProteins: Structure, Function, and Bioinformaticsen
dc.identifier.pmcidPMC4406047en
dc.contributor.institutionGenome Center University of California, Davis, Davis, California, 95616.en
kaust.grant.numberKUK-I1–012-43en

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