title: PconsC: combination of direct information methods and alignments improves contact prediction.
abstract: CONCLUSIONS
  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.
  
  
  BACKGROUND
  The source code for PconsC along with supplementary data is freely available at http://c.pcons.net/
  
  
  BACKGROUND
  arne@bioinfo.se
  
  
  BACKGROUND
  Supplementary data are available at Bioinformatics online.
authors: Department of Biochemistry and Biophysics, Stockholm University, 10691 Stockholm, Sweden.
authors: Marcin J
authors: MJ
authors: Skwark
authors: Abbi
authors: A
authors: Abdel-Rehim
authors: Arne
authors: A
authors: Elofsson
mesh_terms: D000465:Algorithms; D011487:Protein Conformation; D011506:Proteins / Q000737:chemistry; D016415:Sequence Alignment / Q000379:methods*; D020539:Sequence Analysis, Protein
chemical_list: D011506:Proteins