title: Automated server predictions in CASP7.
abstract: With each round of CASP (Critical Assessment of Techniques for Protein Structure Prediction), automated prediction servers have played an increasingly important role. Today, most protein structure prediction approaches in some way depend on automated methods for fold recognition or model building. The accuracy of server predictions has significantly increased over the last years, and, in CASP7, we observed a continuation of this trend. In the template-based modeling category, the best prediction server was ranked third overall, i.e. it outperformed all but two of the human participating groups. This server also ranked among the very best predictors in the free modeling category as well, being clearly beaten by only one human group. In the high accuracy (HA) subset of TBM, two of the top five groups were servers. This article summarizes the contribution of automated structure prediction servers in the CASP7 experiment, with emphasis on 3D structure prediction, as well as information on their prediction scope and public availability.
authors: Biozentrum, University of Basel, Basel, Switzerland.
authors: James N D
authors: JN
authors: Battey
authors: Jürgen
authors: J
authors: Kopp
authors: Lorenza
authors: L
authors: Bordoli
authors: Randy J
authors: RJ
authors: Read
authors: Neil D
authors: ND
authors: Clarke
authors: Torsten
authors: T
authors: Schwede
mesh_terms: D019295:Computational Biology / Q000379:methods*; D020407:Internet; D008958:Models, Molecular; D011487:Protein Conformation; D011506:Proteins / Q000737:chemistry; D012984:Software
chemical_list: D011506:Proteins