title: Pcons.net: protein structure prediction meta server.
abstract: The Pcons.net Meta Server (http://pcons.net) provides improved automated tools for protein structure prediction and analysis using consensus. It essentially implements all the steps necessary to produce a high quality model of a protein. The whole process is fully automated and a potential user only submits the protein sequence. For PSI-BLAST detectable targets, an accurate model is generated within minutes of submission. For more difficult targets the sequence is automatically submitted to publicly available fold-recognition servers that use more advanced approaches to find distant structural homologs. The results from these servers are analyzed and assessed for structural correctness using Pcons and ProQ; and the user is presented with a ranked list of possible models. In addition, if the protein sequence contains more than one domain, these are automatically parsed out and resubmitted to the server as individual queries.
authors.affiliation: Department of Biochemistry, University of Washington, Box 357350, Seattle, WA 98195, USA. bjornwa@u.washington.edu
authors.forename: Björn
authors.initials: B
authors.lastname: Wallner
authors.forename: Per
authors.initials: P
authors.lastname: Larsson
authors.forename: Arne
authors.initials: A
authors.lastname: Elofsson
mesh_terms: D000465:Algorithms; D000595:Amino Acid Sequence; D001331:Automation; D019295:Computational Biology / Q000379:methods*; D030562:Databases, Protein; D001330:Electronic Data Processing; D008958:Models, Molecular; D015233:Models, Statistical; D016571:Neural Networks, Computer; D017510:Protein Folding; D017433:Protein Structure, Secondary; D017434:Protein Structure, Tertiary; D011506:Proteins / Q000737:chemistry* / Q000235:genetics; D012680:Sensitivity and Specificity; D012984:Software
chemical_list: D011506:Proteins