article Open AccessTop 1% cited
Accurate De Novo Prediction of Protein Contact Map by Ultra-Deep Learning Model
PLoS Computational Biology · 2017 · Vol. 13(1) · pp. e1005324–e1005324
Sheng Wang(Toyota Technological Institute at Chicago)Siqi Sun(Toyota Technological Institute at Chicago)Zhen Li(Toyota Technological Institute at Chicago)Renyu Zhang(Toyota Technological Institute at Chicago)Jinbo Xu✉(Toyota Technological Institute at Chicago)
Abstract
http://raptorx.uchicago.edu/ContactMap/.
Protein Structure and DynamicsRNA and protein synthesis mechanismsMachine Learning in BioinformaticsResidualArtificial intelligenceDeep learningComputer sciencePairwise comparisonConvolutional neural networkProtein structure predictionCASPArtificial neural networkTransformation (genetics)
MeSH terms
Machine LearningAlgorithmsProtein ConformationProteinsNeural Networks, ComputerComputational BiologySequence Analysis, ProteinDatabases, Protein
Funding
- National Science Foundation
- Nvidia
- National Institutes of Health
- Directorate for Biological Sciences
- National Institute of General Medical Sciences
Citations
977
FWCI
48.47
field-weighted impact
References
57
Percentile
100%
vs. same field & year
Citations per year
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References
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Nature Methods · 2011 · 2,461 citations
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Proteins Structure Function and Bioinformatics · 2013 · 689 citations
Improved contact prediction in proteins: Using pseudolikelihoods to infer Potts models
Physical Review E · 2013 · 727 citations
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Proteins Structure Function and Bioinformatics · 2004 · 2,431 citations
Correlated mutations and residue contacts in proteins
Proteins Structure Function and Bioinformatics · 1994 · 886 citations
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