Accurate contact predictions using covariation techniques and machine learning
Published 2015 View Full Article
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Title
Accurate contact predictions using covariation techniques and machine learning
Authors
Keywords
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Journal
PROTEINS-STRUCTURE FUNCTION AND BIOINFORMATICS
Volume 84, Issue -, Pages 145-151
Publisher
Wiley
Online
2015-07-24
DOI
10.1002/prot.24863
References
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Related references
Note: Only part of the references are listed.- CCMpred—fast and precise prediction of protein residue–residue contacts from correlated mutations
- (2014) Stefan Seemayer et al. BIOINFORMATICS
- MetaPSICOV: combining coevolution methods for accurate prediction of contacts and long range hydrogen bonding in proteins
- (2014) David T. Jones et al. BIOINFORMATICS
- FreeContact: fast and free software for protein contact prediction from residue co-evolution
- (2014) László Kaján et al. BMC BIOINFORMATICS
- Fast pseudolikelihood maximization for direct-coupling analysis of protein structure from many homologous amino-acid sequences
- (2014) Magnus Ekeberg et al. JOURNAL OF COMPUTATIONAL PHYSICS
- De Novo Structure Prediction of Globular Proteins Aided by Sequence Variation-Derived Contacts
- (2014) Tomasz Kosciolek et al. PLoS One
- Improved Contact Predictions Using the Recognition of Protein Like Contact Patterns
- (2014) Marcin J. Skwark et al. PLoS Computational Biology
- Prediction of contacts from correlated sequence substitutions
- (2013) William R Taylor et al. CURRENT OPINION IN STRUCTURAL BIOLOGY
- Improved contact prediction in proteins: Using pseudolikelihoods to infer Potts models
- (2013) Magnus Ekeberg et al. PHYSICAL REVIEW E
- Assessing the utility of coevolution-based residue-residue contact predictions in a sequence- and structure-rich era
- (2013) H. Kamisetty et al. PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
- Coevolutionary signals across protein lineages help capture multiple protein conformations
- (2013) F. Morcos et al. PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
- One contact for every twelve residues allows robust and accurate topology-level protein structure modeling
- (2013) David E. Kim et al. PROTEINS-STRUCTURE FUNCTION AND BIOINFORMATICS
- Evaluation of residue-residue contact prediction in CASP10
- (2013) Bohdan Monastyrskyy et al. PROTEINS-STRUCTURE FUNCTION AND BIOINFORMATICS
- Protein structure prediction from sequence variation
- (2012) Debora S Marks et al. NATURE BIOTECHNOLOGY
- Accurate de novo structure prediction of large transmembrane protein domains using fragment-assembly and correlated mutation analysis
- (2012) T. Nugent et al. PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
- PSICOV: precise structural contact prediction using sparse inverse covariance estimation on large multiple sequence alignments
- (2011) David T. Jones et al. BIOINFORMATICS
- HHblits: lightning-fast iterative protein sequence searching by HMM-HMM alignment
- (2011) Michael Remmert et al. NATURE METHODS
- HMMER web server: interactive sequence similarity searching
- (2011) R. D. Finn et al. NUCLEIC ACIDS RESEARCH
- Protein 3D Structure Computed from Evolutionary Sequence Variation
- (2011) Debora S. Marks et al. PLoS One
- Direct-coupling analysis of residue coevolution captures native contacts across many protein families
- (2011) F. Morcos et al. PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
- Transmembrane protein topology prediction using support vector machines
- (2009) Timothy Nugent et al. BMC BIOINFORMATICS
- Identification of direct residue contacts in protein-protein interaction by message passing
- (2008) M. Weigt et al. PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
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