Handle URI:
http://hdl.handle.net/10754/598246
Title:
Evaluation of disorder predictions in CASP9
Authors:
Monastyrskyy, Bohdan; Fidelis, Krzysztof; Moult, John; Tramontano, Anna; Kryshtafovych, Andriy
Abstract:
Lack of stable three-dimensional structure, or intrinsic disorder, is a common phenomenon in proteins. Naturally, unstructured regions are proven to be essential for carrying function by many proteins, and therefore identification of such regions is an important issue. CASP has been assessing the state of the art in predicting disorder regions from amino acid sequence since 2002. Here, we present the results of the evaluation of the disorder predictions submitted to CASP9. The assessment is based on the evaluation measures and procedures used in previous CASPs. The balanced accuracy and the Matthews correlation coefficient were chosen as basic measures for evaluating the correctness of binary classifications. The area under the receiver operating characteristic curve was the measure of choice for evaluating probability-based predictions of disorder. The CASP9 methods are shown to perform slightly better than the CASP7 methods but not better than the methods in CASP8. It was also shown that capability of most CASP9 methods to predict disorder decreases with increasing minimum disorder segment length.
Citation:
Monastyrskyy B, Fidelis K, Moult J, Tramontano A, Kryshtafovych A (2011) Evaluation of disorder predictions in CASP9. Proteins: Structure, Function, and Bioinformatics 79: 107–118. Available: http://dx.doi.org/10.1002/prot.23161.
Publisher:
Wiley-Blackwell
Journal:
Proteins: Structure, Function, and Bioinformatics
KAUST Grant Number:
KUK-I1-012-43
Issue Date:
2011
DOI:
10.1002/prot.23161
PubMed ID:
21928402
PubMed Central ID:
PMC3212657
Type:
Article
ISSN:
0887-3585
Sponsors:
Grant sponsor: US National Library of Medicine (NIH/NLM); Grant number: LM007085; Grant sponsor: King Abdullah University of Science and Technology (KAUST); Grant number: KUK-I1-012-43.
Appears in Collections:
Publications Acknowledging KAUST Support

Full metadata record

DC FieldValue Language
dc.contributor.authorMonastyrskyy, Bohdanen
dc.contributor.authorFidelis, Krzysztofen
dc.contributor.authorMoult, Johnen
dc.contributor.authorTramontano, Annaen
dc.contributor.authorKryshtafovych, Andriyen
dc.date.accessioned2016-02-25T13:17:19Zen
dc.date.available2016-02-25T13:17:19Zen
dc.date.issued2011en
dc.identifier.citationMonastyrskyy B, Fidelis K, Moult J, Tramontano A, Kryshtafovych A (2011) Evaluation of disorder predictions in CASP9. Proteins: Structure, Function, and Bioinformatics 79: 107–118. Available: http://dx.doi.org/10.1002/prot.23161.en
dc.identifier.issn0887-3585en
dc.identifier.pmid21928402en
dc.identifier.doi10.1002/prot.23161en
dc.identifier.urihttp://hdl.handle.net/10754/598246en
dc.description.abstractLack of stable three-dimensional structure, or intrinsic disorder, is a common phenomenon in proteins. Naturally, unstructured regions are proven to be essential for carrying function by many proteins, and therefore identification of such regions is an important issue. CASP has been assessing the state of the art in predicting disorder regions from amino acid sequence since 2002. Here, we present the results of the evaluation of the disorder predictions submitted to CASP9. The assessment is based on the evaluation measures and procedures used in previous CASPs. The balanced accuracy and the Matthews correlation coefficient were chosen as basic measures for evaluating the correctness of binary classifications. The area under the receiver operating characteristic curve was the measure of choice for evaluating probability-based predictions of disorder. The CASP9 methods are shown to perform slightly better than the CASP7 methods but not better than the methods in CASP8. It was also shown that capability of most CASP9 methods to predict disorder decreases with increasing minimum disorder segment length.en
dc.description.sponsorshipGrant sponsor: US National Library of Medicine (NIH/NLM); Grant number: LM007085; Grant sponsor: King Abdullah University of Science and Technology (KAUST); Grant number: KUK-I1-012-43.en
dc.publisherWiley-Blackwellen
dc.subjectIntrinsically Disordered Proteinsen
dc.subjectCaspen
dc.subjectAssessment Of Disorder Predictionen
dc.subjectRediction Of Disordered Regionsen
dc.subjectUnstructured Proteinsen
dc.titleEvaluation of disorder predictions in CASP9en
dc.typeArticleen
dc.identifier.journalProteins: Structure, Function, and Bioinformaticsen
dc.identifier.pmcidPMC3212657en
dc.contributor.institutionGenome Center, University of California-Davis, 451 Health Sciences Drive, Davis, CA 95616, USAen
kaust.grant.numberKUK-I1-012-43en

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