title: Evaluation of disorder predictions in CASP9.
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.
authors.affiliation: Genome Center, University of California-Davis, 451 Health Sciences Drive, Davis, CA 95616, USA
authors.forename: Bohdan
authors.initials: B
authors.lastname: Monastyrskyy
authors.forename: Krzysztof
authors.initials: K
authors.lastname: Fidelis
authors.forename: John
authors.initials: J
authors.lastname: Moult
authors.forename: Anna
authors.initials: A
authors.lastname: Tramontano
authors.forename: Andriy
authors.initials: A
authors.lastname: Kryshtafovych
mesh_terms: D000595:Amino Acid Sequence; D019295:Computational Biology / Q000379:methods*; D015233:Models, Statistical; D011487:Protein Conformation; D011506:Proteins / Q000737:chemistry*; D012984:Software
chemical_list: D011506:Proteins