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Assessment of protein disorder region predictions in CASP10
Author(s) -
Monastyrskyy Bohdan,
Kryshtafovych Andriy,
Moult John,
Tramontano Anna,
Fidelis Krzysztof
Publication year - 2014
Publication title -
proteins: structure, function, and bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.699
H-Index - 191
eISSN - 1097-0134
pISSN - 0887-3585
DOI - 10.1002/prot.24391
Subject(s) - receiver operating characteristic , binary number , computer science , correlation , statistics , artificial intelligence , data mining , machine learning , mathematics , geometry , arithmetic
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. Proteins 2014; 82(Suppl 2):127–137. © 2013 Wiley Periodicals, Inc.