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Bioinformatics Vol. 17 no. 12 2001
Pages 1242-1243
© 2001 Oxford University Press

Applications Note

EVA: continuous automatic evaluation of protein structure prediction servers

Volker A. Eyrich 1, Marc A. Martí-Renom 2, Dariusz Przybylski 3, Mallur S. Madhusudhan 2, András Fiser 2, Florencio Pazos 4, Alfonso Valencia 4, Andrej Sali 2 and Burkhard Rost 3,*

1 Columbia University, Department of Chemistry, 3000 Broadway MC 3136, New York, NY 10027, USA
2 The Rockefeller University, Laboratory of Molecular Biophysics, Pels Family Center for Biochemistry and Structural Biology, 1230 York Avenue, New York, NY 10021-6399, USA
3 CUBIC Columbia University, Department of Biochemistry and Molecular Biophysics, 650 West 168th Street, New York, NY 10032, USA
4 Protein Design Group, CNB-CSIC, Cantoblanco, Madrid 28049, Spain

Received on February 20, 2001 ; revised on May 28, 2001 ; accepted on July 4, 2001

Summary: Evaluation of protein structure prediction methods is difficult and time-consuming. Here, we describe EVA, a web server for assessing protein structure prediction methods, in an automated, continuous and large-scale fashion. Currently, EVA evaluates the performance of a variety of prediction methods available through the internet. Every week, the sequences of the latest experimentally determined protein structures are sent to prediction servers, results are collected, performance is evaluated, and a summary is published on the web. EVA has so far collected data for more than 3000 protein chains. These results may provide valuable insight to both developers and users of prediction methods.

Availability: http://cubic.bioc.columbia.edu/eva.

Contact: eva{at}cubic.bioc.columbia.edu

* To whom correspondence should be addressed.


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