Assessment of model accuracy estimations in CASP12

Kryshtafovych, Andriy and Monastyrskyy, Bohdan and Fidelis, Krzysztof and Schwede, Torsten and Tramontano, Anna. (2017) Assessment of model accuracy estimations in CASP12. Proteins, 86 (S1). pp. 345-360.

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Official URL: http://edoc.unibas.ch/56029/

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The record high 42 model accuracy estimation methods were tested in CASP12. The paper presents results of the assessment of these methods in the whole-model and per-residue accuracy modes. Scores from four different model evaluation packages were used as the 'ground truth' for assessing accuracy of methods' estimates. They include a rigid-body score - GDT_TS, and three local-structure based scores - LDDT, CAD and SphereGrinder. The ability of methods to identify best models from among several available, predict model's absolute accuracy score, distinguish between good and bad models, predict accuracy of the coordinate error self-estimates, and discriminate between reliable and unreliable regions in the models was assessed. Single-model methods advanced to the point where they are better than clustering methods in picking the best models from decoy sets. On the other hand, consensus methods, taking advantage of the availability of large number of models for the same target protein, are still better in distinguishing between good and bad models and predicting local accuracy of models. The best accuracy estimation methods were shown to perform better with respect to the frozen in time reference clustering method and the results of the best method in the corresponding class of methods from the previous CASP. Top performing single-model methods were shown to do better than all but three CASP12 tertiary structure predictors when evaluated as model selectors.
Faculties and Departments:05 Faculty of Science > Departement Biozentrum > Computational & Systems Biology > Bioinformatics (Schwede)
10 Zentrale universitäre Einrichtungen > sciCORE
UniBasel Contributors:Schwede, Torsten
Item Type:Article, refereed
Article Subtype:Research Article
Note:Publication type according to Uni Basel Research Database: Journal article
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Last Modified:13 Apr 2018 12:21
Deposited On:23 Oct 2017 10:12

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