eprintid: 1460206
rev_number: 58
eprint_status: archive
userid: 608
dir: disk0/01/46/02/06
datestamp: 2015-03-20 16:29:34
lastmod: 2021-09-20 00:06:45
status_changed: 2015-03-20 16:29:34
type: article
metadata_visibility: show
item_issues_count: 0
creators_name: Jones, DT
creators_name: Singh, T
creators_name: Kosciolek, T
creators_name: Tetchner, S
title: MetaPSICOV: combining coevolution methods for accurate prediction of contacts and long range hydrogen bonding in proteins.
divisions: UCL
divisions: B02
divisions: C08
divisions: B04
divisions: C05
divisions: F48
note: This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. MetaPSICOV is available as a freely available web server at http://bioinf.cs.ucl.ac.uk/MetaPSICOV. Raw data (predicted contact lists and 3D models) and source code
can be downloaded from http://bioinf.cs.ucl.ac.uk/downloads/MetaPSICOV.
abstract: Recent developments of statistical techniques to infer direct evolutionary couplings between residue pairs have rendered covariation-based contact prediction a viable means for accurate 3D modelling of proteins, with no information other than the sequence required. To extend the usefulness of contact prediction, we have designed a new meta-predictor (MetaPSICOV) which combines three distinct approaches for inferring covariation signals from multiple sequence alignments, considers a broad range of other sequence-derived features and, uniquely, a range of metrics which describe both the local and global quality of the input multiple sequence alignment. Finally, we use a two-stage predictor, where the second stage filters the output of the first stage. This two-stage predictor is additionally evaluated on its ability to accurately predict the long range network of hydrogen bonds, including correctly assigning the donor and acceptor residues.
date: 2014-11-26
official_url: http://dx.doi.org/10.1093/bioinformatics/btu791
vfaculties: VENG
oa_status: green
full_text_type: other
primo: open
primo_central: open_green
article_type_text: JOURNAL ARTICLE
verified: verified_manual
elements_source: PubMed
elements_id: 996068
doi: 10.1093/bioinformatics/btu791
pii: btu791
language_elements: ENG
lyricists_name: Jones, David
lyricists_name: Singh, Tanya
lyricists_id: DTJON81
lyricists_id: TSING03
full_text_status: public
publication: Bioinformatics
issn: 1367-4803
citation:        Jones, DT;    Singh, T;    Kosciolek, T;    Tetchner, S;      (2014)    MetaPSICOV: combining coevolution methods for accurate prediction of contacts and long range hydrogen bonding in proteins.                   Bioinformatics        10.1093/bioinformatics/btu791 <https://doi.org/10.1093/bioinformatics%2Fbtu791>.       Green open access   
 
document_url: https://discovery.ucl.ac.uk/id/eprint/1460206/1/metapsicov_v8.18.pdf
document_url: https://discovery.ucl.ac.uk/id/eprint/1460206/3/metapsicov_supplementary_v0.03.pdf