General Information
| Description | Combination of direct information methods and alignments improves contact prediction |
| Homepage | http://c.pcons.net/ |
Publications
PconsC: combination of direct information methods and alignments improves contact prediction
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.
Related Tools
PSICOV
Published November 2011
Precise structural contact prediction using sparse inverse covariance estimation on large multiple sequence alignments
RC
Published April 2016
Improving ab initio residue contact map prediction using dynamic fusion strategy and Gaussian noise filter
QAcon
Published November 2016
Single model quality assessment using protein structural and contact information with machine learning techniques
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