Evolutionary Coupling Analysis
Evolutionary Coupling Analysis is a computational method in structural bioinformatics that identifies co-evolving amino acid residues in protein families by analyzing patterns of sequence variation across homologs, thereby inferring spatial proximities and functional dependencies for secondary structure prediction.
66
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5.5K
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258
Authors
134
Institutions
Publications per year
2017–2026
37
Variants
Eca
Parents
66
Protein 3D Structure Computed from Evolutionary Sequence Variation
Debora S. Marks, Lucy J. Colwell, Robert P. Sheridan et al. · PLoS ONE · 2011 · 1.2K citations · Full text
Accurate De Novo Prediction of Protein Contact Map by Ultra-Deep Learning Model
Sheng Wang, Siqi Sun, Zhen Li et al. · PLoS Computational Biology · 2017 · 988 citations · Full text
The EVcouplings Python framework for coevolutionary sequence analysis
Thomas A. Hopf, Anna G. Green, Benjamin Schubert et al. · Bioinformatics · 2018 · 326 citations · Full text
Metabolic rate evolves rapidly and in parallel with the pace of life history
Sonya K. Auer, Cynthia Dick, Neil B. Metcalfe et al. · Nature Communications · 2017 · 181 citations · Full text
Domain structural class prediction
K.-C. Chou, Gerald M. Maggiora · Protein Engineering Design and Selection · 1998 · 159 citations
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Harvard University
Cambridge, United States
11 h-index
63 publications
10K citations
Center for Systems Biology
Boston, United States
8 h-index
41 publications
8K citations
Memorial Sloan Kettering Cancer Center
New York, United States
6 h-index
20 publications
3.8K citations
Simula Research Laboratory
Oslo, Norway
5 h-index
16 publications
359 citations
Technical University of Munich
Munich, Germany
5 h-index
8 publications
494 citations
Toyota Technological Institute at Chicago
Chicago, United States
4 h-index
17 publications
5.9K citations
Dana-Farber Cancer Institute
Boston, United States
4 h-index
11 publications
814 citations
Rutgers, The State University of New Jersey
New Brunswick, United States
3 h-index
5 publications
300 citations
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4 publications · 287 citations
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4 publications · 521 citations
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3 publications · 1K citations
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Repository · 3 publications · 105 citations
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PNAS · 3 publications · 143 citations
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