<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Koh, I. Y.</style></author><author><style face="normal" font="default" size="100%">Eyrich, V. A.</style></author><author><style face="normal" font="default" size="100%">M. A. Marti-Renom</style></author><author><style face="normal" font="default" size="100%">Przybylski, D.</style></author><author><style face="normal" font="default" size="100%">Madhusudhan, M. S.</style></author><author><style face="normal" font="default" size="100%">Eswar, N.</style></author><author><style face="normal" font="default" size="100%">Grana, O.</style></author><author><style face="normal" font="default" size="100%">Pazos, F.</style></author><author><style face="normal" font="default" size="100%">Valencia, A.</style></author><author><style face="normal" font="default" size="100%">Sali, A.</style></author><author><style face="normal" font="default" size="100%">Rost, B.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">EVA: Evaluation of protein structure prediction servers</style></title><secondary-title><style face="normal" font="default" size="100%">Nucleic Acids Res</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Automation Databases</style></keyword><keyword><style  face="normal" font="default" size="100%">Protein</style></keyword><keyword><style  face="normal" font="default" size="100%">Protein Internet *Protein Conformation Protein Folding Protein Structure</style></keyword><keyword><style  face="normal" font="default" size="100%">Protein Structural Homology</style></keyword><keyword><style  face="normal" font="default" size="100%">Secondary Proteins/chemistry Reproducibility of Results *Sequence Analysis</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2003</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&amp;db=PubMed&amp;dopt=Citation&amp;list_uids=12824315</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">13</style></number><volume><style face="normal" font="default" size="100%">31</style></volume><pages><style face="normal" font="default" size="100%">3311-5</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">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.</style></abstract><notes><style face="normal" font="default" size="100%">Koh, Ingrid Y Y Eyrich, Volker A Marti-Renom, Marc A Przybylski, Dariusz Madhusudhan, Mallur S Eswar, Narayanan Grana, Osvaldo Pazos, Florencio Valencia, Alfonso Sali, Andrej Rost, Burkhard 1-P50-GM62413-01/GM/NIGMS NIH HHS/United States 5-P20-LM7276/LM/NLM NIH HHS/United States P50 GM62529/GM/NIGMS NIH HHS/United States R01 GM54762/GM/NIGMS NIH HHS/United States R01-GM63029-01/GM/NIGMS NIH HHS/United States Research Support, Non-U.S. Gov’t Research Support, U.S. Gov’t, Non-P.H.S. Research Support, U.S. Gov’t, P.H.S. England Nucleic acids research Nucleic Acids Res. 2003 Jul 1;31(13):3311-5.</style></notes></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">M. A. Marti-Renom</style></author><author><style face="normal" font="default" size="100%">Madhusudhan, M. S.</style></author><author><style face="normal" font="default" size="100%">Fiser, A.</style></author><author><style face="normal" font="default" size="100%">Rost, B.</style></author><author><style face="normal" font="default" size="100%">Sali, A.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Reliability of assessment of protein structure prediction methods</style></title><secondary-title><style face="normal" font="default" size="100%">Structure</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">*Computer Simulation Humans *Models</style></keyword><keyword><style  face="normal" font="default" size="100%">Molecular *Protein Conformation Proteins/*chemistry Reproducibility of Results</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2002</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&amp;db=PubMed&amp;dopt=Citation&amp;list_uids=12005441</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">3</style></number><volume><style face="normal" font="default" size="100%">10</style></volume><pages><style face="normal" font="default" size="100%">435-40</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;The reliability of ranking of protein structure modeling methods is assessed. The assessment is based on the parametric Student’s t test and the nonparametric Wilcox signed rank test of statistical significance of the difference between paired samples. The approach is applied to the ranking of the comparative modeling methods tested at the fourth meeting on Critical Assessment of Techniques for Protein Structure Prediction (CASP). It is shown that the 14 CASP4 test sequences may not be sufficient to reliably distinguish between the top eight methods, given the model quality differences and their standard deviations. We suggest that CASP needs to be supplemented by an assessment of protein structure prediction methods that is automated, continuous in time, based on several criteria applied to a large number of models, and with quantitative statistical reliability assigned to each characterization.&lt;/p&gt;</style></abstract><notes><style face="normal" font="default" size="100%">&lt;p&gt;Marti-Renom, Marc A Madhusudhan, M S Fiser, Andras Rost, Burkhard Sali, Andrej GM 54762/GM/NIGMS NIH HHS/United States GM62413/GM/NIGMS NIH HHS/United States Comparative Study Research Support, Non-U.S. Gov’t Research Support, U.S. Gov’t, P.H.S. United States Structure (London, England : 1993) Structure. 2002 Mar;10(3):435-40.&lt;/p&gt;</style></notes></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Eyrich, V. A.</style></author><author><style face="normal" font="default" size="100%">M. A. Marti-Renom</style></author><author><style face="normal" font="default" size="100%">Przybylski, D.</style></author><author><style face="normal" font="default" size="100%">Madhusudhan, M. S.</style></author><author><style face="normal" font="default" size="100%">Fiser, A.</style></author><author><style face="normal" font="default" size="100%">Pazos, F.</style></author><author><style face="normal" font="default" size="100%">Valencia, A.</style></author><author><style face="normal" font="default" size="100%">Sali, A.</style></author><author><style face="normal" font="default" size="100%">Rost, B.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">EVA: continuous automatic evaluation of protein structure prediction servers</style></title><secondary-title><style face="normal" font="default" size="100%">Bioinformatics</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Automation Internet *Protein Conformation Proteins/*analysis *Software</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2001</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&amp;db=PubMed&amp;dopt=Citation&amp;list_uids=11751240</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">12</style></number><volume><style face="normal" font="default" size="100%">17</style></volume><pages><style face="normal" font="default" size="100%">1242-3</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">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.edu</style></abstract><notes><style face="normal" font="default" size="100%">Eyrich, V A Marti-Renom, M A Przybylski, D Madhusudhan, M S Fiser, A Pazos, F Valencia, A Sali, A Rost, B England Bioinformatics (Oxford, England) Bioinformatics. 2001 Dec;17(12):1242-3.</style></notes></record></records></xml>