Data-driven high-throughput prediction of the 3-D structure of small molecules: Review and progress

Journal of Chemical Information and Modeling

Volumn 51, Issue 4, 2011, Pages 760-776

  Andronico, Alessio ^a   Randall, Arlo ^a   Benz, Ryan W ^a,b   Baldi, Pierre ^a  

^a UNIVERSITY OF CALIFORNIA   (United States)

^b Currently with Applied Proteomics   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

FORECASTING; METALS; MOLECULES; ORGANOMETALLICS; PORTALS;

ACCURATE PREDICTION; BIOLOGICAL PROPERTIES; CAMBRIDGE STRUCTURAL DATABASE; HIGH-THROUGHPUT METHOD; PREDICTION METHODS; STATE OF THE ART; SYSTEM'S PERFORMANCE; TARGET SPECIFICATIONS;

DISTRIBUTED DATABASE SYSTEMS;

ALGORITHM; AUTOMATED PATTERN RECOGNITION; CHEMICAL STRUCTURE; CHEMISTRY; CONFORMATION; FACTUAL DATABASE; INFORMATION SCIENCE; METHODOLOGY; REVIEW; STATISTICAL MODEL;

ALGORITHMS; CHEMISTRY; DATABASES, FACTUAL; INFORMATICS; MODELS, MOLECULAR; MODELS, STATISTICAL; MOLECULAR CONFORMATION; PATTERN RECOGNITION, AUTOMATED;

EID: 79955389305     PISSN: 15499596     EISSN: 1549960X     Source Type: Journal    
DOI: 10.1021/ci100223t     Document Type: Article

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