| Literature DB >> 11751240 |
V A Eyrich1, M A Martí-Renom, D Przybylski, M S Madhusudhan, A Fiser, F Pazos, A Valencia, A Sali, B Rost.
Abstract
UNLABELLED: 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@cubic.bioc.columbia.eduEntities:
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Year: 2001 PMID: 11751240 DOI: 10.1093/bioinformatics/17.12.1242
Source DB: PubMed Journal: Bioinformatics ISSN: 1367-4803 Impact factor: 6.937