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    Evaluation of CASP8 model quality predictions

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    Type
    Article
    Authors
    Cozzetto, Domenico
    Kryshtafovych, Andriy cc
    Tramontano, Anna
    KAUST Grant Number
    KUK-11-012-43
    Date
    2009-07-14
    Online Publication Date
    2009-07-14
    Print Publication Date
    2009
    Permanent link to this record
    http://hdl.handle.net/10754/598244
    
    Metadata
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    Abstract
    The model quality assessment problem consists in the a priori estimation of the overall and per-residue accuracy of protein structure predictions. Over the past years, a number of methods have been developed to address this issue and CASP established a prediction category to evaluate their performance in 2006. In 2008 the experiment was repeated and its results are reported here. Participants were invited to infer the correctness of the protein models submitted by the registered automatic servers. Estimates could apply to both whole models and individual amino acids. Groups involved in the tertiary structure prediction categories were also asked to assign local error estimates to each predicted residue in their own models and their results are also discussed here. The correlation between the predicted and observed correctness measures was the basis of the assessment of the results. We observe that consensus-based methods still perform significantly better than those accepting single models, similarly to what was concluded in the previous edition of the experiment. © 2009 WILEY-LISS, INC.
    Citation
    Cozzetto D, Kryshtafovych A, Tramontano A (2009) Evaluation of CASP8 model quality predictions. Proteins: Structure, Function, and Bioinformatics 77: 157–166. Available: http://dx.doi.org/10.1002/prot.22534.
    Sponsors
    Grant sponsor: KAUST; Grant number: KUK-11-012-43; Grant sponsor: MIUR (FIRB Rete Italiana di Proteomica), EMBO; Grant sponsor: The US National Library of Medicine; Grant number: LM-7085
    Publisher
    Wiley
    Journal
    Proteins: Structure, Function, and Bioinformatics
    DOI
    10.1002/prot.22534
    PubMed ID
    19714774
    ae974a485f413a2113503eed53cd6c53
    10.1002/prot.22534
    Scopus Count
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