| Literature DB >> 23658418 |
Marcin J Skwark1, Abbi Abdel-Rehim, Arne Elofsson.
Abstract
SUMMARY: Recently, several new contact prediction methods have been published. They use (i) large sets of multiple aligned sequences and (ii) assume that correlations between columns in these alignments can be the results of indirect interaction. These methods are clearly superior to earlier methods when it comes to predicting contacts in proteins. Here, we demonstrate that combining predictions from two prediction methods, PSICOV and plmDCA, and two alignment methods, HHblits and jackhmmer at four different e-value cut-offs, provides a relative improvement of 20% in comparison with the best single method, exceeding 70% correct predictions for one contact prediction per residue. AVAILABILITY: The source code for PconsC along with supplementary data is freely available at http://c.pcons.net/ CONTACT: arne@bioinfo.se SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.Mesh:
Substances:
Year: 2013 PMID: 23658418 DOI: 10.1093/bioinformatics/btt259
Source DB: PubMed Journal: Bioinformatics ISSN: 1367-4803 Impact factor: 6.937