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EVA:蛋白质结构预测服务器评估

EVA: Evaluation of protein structure prediction servers.

作者信息

Koh Ingrid Y Y, Eyrich Volker A, Marti-Renom Marc A, Przybylski Dariusz, Madhusudhan Mallur S, Eswar Narayanan, Graña Osvaldo, Pazos Florencio, Valencia Alfonso, Sali Andrej, Rost Burkhard

机构信息

Columbia University Center for Computational Biology and Bioinformatics (C2B2), Russ Berrie Pavilion, 1150 St Nicholas Avenue, New York, NY 10032, USA.

出版信息

Nucleic Acids Res. 2003 Jul 1;31(13):3311-5. doi: 10.1093/nar/gkg619.

Abstract

EVA (http://cubic.bioc.columbia.edu/eva/) is a web server for evaluation of the accuracy of automated protein structure prediction methods. The evaluation is updated automatically each week, to cope with the large number of existing prediction servers and the constant changes in the prediction methods. EVA currently assesses servers for secondary structure prediction, contact prediction, comparative protein structure modelling and threading/fold recognition. Every day, sequences of newly available protein structures in the Protein Data Bank (PDB) are sent to the servers and their predictions are collected. The predictions are then compared to the experimental structures once a week; the results are published on the EVA web pages. Over time, EVA has accumulated prediction results for a large number of proteins, ranging from hundreds to thousands, depending on the prediction method. This large sample assures that methods are compared reliably. As a result, EVA provides useful information to developers as well as users of prediction methods.

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