EVA: Continuous automatic evaluation of protein structure prediction servers

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

Research output: Contribution to journalArticle

164 Scopus citations

Abstract

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.

Original languageEnglish (US)
Pages (from-to)1242-1243
Number of pages2
JournalBioinformatics
Volume17
Issue number12
DOIs
StatePublished - Jan 1 2002

ASJC Scopus subject areas

  • Statistics and Probability
  • Biochemistry
  • Molecular Biology
  • Computer Science Applications
  • Computational Theory and Mathematics
  • Computational Mathematics

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    Eyrich, V. A., Martí-Renom, M. A., Przybylski, D., Madhusudhan, M. S., Fiser, A., Pazos, F., Valencia, A., Sali, A., & Rost, B. (2002). EVA: Continuous automatic evaluation of protein structure prediction servers. Bioinformatics, 17(12), 1242-1243. https://doi.org/10.1093/bioinformatics/17.12.1242