Protein sequence‐to‐structure learning: Is this the end(‐to‐end revolution)?-Reference-Cited by-同舟云学术

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Protein sequence‐to‐structure learning: Is this the end(‐to‐end revolution)?

Published:2021-09-22 Issue:12 Volume:89 Page:1770-1786
ISSN:0887-3585
Container-title:Proteins: Structure, Function, and Bioinformatics
language:en
Short-container-title:Proteins

Author:

Laine Elodie¹^ORCID,Eismann Stephan²,Elofsson Arne³^ORCID,Grudinin Sergei⁴^ORCID

Affiliation:

1. Sorbonne Université, CNRS, IBPS, Laboratoire de Biologie Computationnelle et Quantitative (LCQB) Paris France

2. Department of Computer Science and Applied Physics Stanford University Stanford California USA

3. Department of Biochemistry and Biophysics and Science for Life Laboratory Stockholm University Solna Sweden

4. Univ. Grenoble Alpes, CNRS, Grenoble INP, LJK Grenoble France

Funder

Agence Nationale de la Recherche

National Institute for Research in Computer Science and Control

Swedish e-Science Research Centre

Publisher

Wiley

Subject

Molecular Biology,Biochemistry,Structural Biology

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/prot.26235

Reference186 articles.

1. Patterns of divergence in homologous proteins as indicators of secondary and tertiary structure: A prediction of the structure of the catalytic domain of protein kinases

2. Correlated mutations and residue contacts in proteins

3. Correlated mutations in models of protein sequences: phylogenetic and structural effects

4. Superadditive correlation;Giraud BG;Phys Rev E Stat Phys Plasmas Fluids Relat Interdiscip Topics,1999

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