Analysis of deep learning methods for blind protein contact prediction in CASP12
Author:
Affiliation:
1. Toyota Technological Institute at Chicago, Chicago, Illinois
Funder
National Institutes of Health
NSF
Publisher
Wiley
Subject
Molecular Biology,Biochemistry,Structural Biology
Link
https://onlinelibrary.wiley.com/doi/pdf/10.1002/prot.25377
Reference27 articles.
1. One contact for every twelve residues allows robust and accurate topology-level protein structure modeling
2. Emerging methods in protein co-evolution
3. Identification of direct residue contacts in protein-protein interaction by message passing
4. CCMpred—fast and precise prediction of protein residue–residue contacts from correlated mutations
5. PSICOV: precise structural contact prediction using sparse inverse covariance estimation on large multiple sequence alignments
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