Benchmarking Inverse Statistical Approaches for Protein Structure and Design with Exactly Solvable Models

PLoS Computational Biology

Volumn 12, Issue 5, 2016, Pages

  Jacquin, Hugo ^a   Gilson, Amy ^b   Shakhnovich, Eugene ^b   Cocco, Simona ^a   Monasson, Rémi ^a  

^a ECOLE NORMALE SUPÉRIEURE   (France)

^b HARVARD UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

POTTS MODEL; PROTEINS; STRUCTURAL DESIGN;

COMPUTATIONAL BIOLOGY; EXACTLY SOLVABLE MODEL; LATTICE PROTEIN MODEL; MULTIPLE SEQUENCE ALIGNMENTS; PROTEIN DESIGN; PROTEIN ENERGETICS; PROTEIN FUNCTIONS; PROTEINS STRUCTURES; STATISTICAL APPROACH; STRUCTURE AND ENERGETICS;

HAMILTONIANS;

COMPETITION; DNA STRUCTURE; PROBABILITY; PROTEIN STRUCTURE; QUALITY CONTROL; SEQUENCE ALIGNMENT; STATISTICAL MODEL; AMINO ACID SEQUENCE; BENCHMARKING; BIOLOGY; CHEMISTRY; COMPUTER SIMULATION; GENETICS; MOLECULAR MODEL; PROTEIN CONFORMATION; PROTEIN FOLDING; STATISTICS AND NUMERICAL DATA;

PROTEIN;

AMINO ACID SEQUENCE; BENCHMARKING; COMPUTATIONAL BIOLOGY; COMPUTER SIMULATION; MODELS, MOLECULAR; MODELS, STATISTICAL; PROTEIN CONFORMATION; PROTEIN FOLDING; PROTEINS; SEQUENCE ALIGNMENT;

EID: 84975833219     PISSN: 1553734X     EISSN: 15537358     Source Type: Journal    
DOI: 10.1371/journal.pcbi.1004889     Document Type: Article

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