A maximum likelihood framework for protein design

BMC Bioinformatics

Volumn 7, Issue , 2006, Pages

  Kleinman, Claudia L ^a   Rodrigue, Nicolas ^a   Bonnard, Cécile ^b   Philippe, Hervé ^a   Lartillot, Nicolas ^b  

^a UNIVERSITÉ DE MONTRÉAL   (Canada)

^b LIRMM   (France)

Author keywords

[No Author keywords available]

Indexed keywords

CLASSICAL POTENTIALS; MARKOV CHAIN MONTE-CARLO; MAXIMUM LIKELIHOOD PRINCIPLE; RELATIVE CONTRIBUTION; STATISTICAL INFERENCE; STATISTICAL POTENTIAL; STRUCTURE PREDICTION; THERMODYNAMIC INTEGRATION;

DESIGN; OPTIMIZATION; STATISTICAL METHODS;

PROTEINS;

PROTEIN; PROTEIN BINDING;

AMINO ACID SEQUENCE; ARTICLE; CONTROLLED STUDY; INTERMETHOD COMPARISON; MAXIMUM LIKELIHOOD METHOD; MONTE CARLO METHOD; PREDICTION; PROBABILITY; PROCESS OPTIMIZATION; PROTEIN DETERMINATION; PROTEIN STRUCTURE; STATISTICAL MODEL; STATISTICAL PARAMETERS; THERMODYNAMICS; THERMOSTABILITY; VALIDATION PROCESS; BINDING SITE; CHEMICAL STRUCTURE; CHEMISTRY; CLASSIFICATION; COMPUTER SIMULATION; DRUG DELIVERY SYSTEM; DRUG DESIGN; MOLECULAR GENETICS; PROCEDURES; PROTEIN ENGINEERING; SEQUENCE ALIGNMENT; SEQUENCE ANALYSIS;

AMINO ACID SEQUENCE; BINDING SITES; COMPUTER SIMULATION; DRUG DELIVERY SYSTEMS; DRUG DESIGN; LIKELIHOOD FUNCTIONS; MODELS, MOLECULAR; MODELS, STATISTICAL; MOLECULAR SEQUENCE DATA; PROTEIN BINDING; PROTEIN ENGINEERING; PROTEINS; SEQUENCE ALIGNMENT; SEQUENCE ANALYSIS, PROTEIN;

EID: 33748205572     PISSN: 14712105     EISSN: 14712105     Source Type: Journal    
DOI: 10.1186/1471-2105-7-326     Document Type: Article

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