Machine learning of chemical reactivity from databases of organic reactions

Journal of Computer-Aided Molecular Design

Volumn 23, Issue 7, 2009, Pages 419-429

  Carrera, Gonçalo V S M ^a   Gupta, Sunil ^a   Aires de Sousa, João ^a  

^a UNIVERSIDADE NOVA DE LISBOA   (Portugal)

Author keywords

Chemical reactivity; Databases; Electrophilicity; Machine learning; MOLMAP

Indexed keywords

AMINO ACIDS; ARTIFICIAL INTELLIGENCE; CHEMICAL REACTIONS; CLASSIFICATION (OF INFORMATION); DECISION TREES; LEARNING SYSTEMS; NIOBIUM COMPOUNDS; SODIUM COMPOUNDS;

DESCRIPTORS; ELECTROPHILICITIES; MACHINE LEARNING TECHNIQUES; MACHINE-LEARNING; MOLECULAR CLASSIFICATION; MOLECULAR DESCRIPTORS; MOLMAP; NEGATIVE INFORMATION; ORGANIC REACTION; WHOLE PROCESS;

DATABASE SYSTEMS;

ACETALDEHYDE; ACETIC ACID; ACETONE; ACROLEIN; ACRYLAMIDE; ACRYLIC ACID; ACRYLIC ACID METHYL ESTER; BENZALDEHYDE; BENZAMIDE; BENZOIC ACID; BENZYLIDENEACETONE; BUTYLAMINE; FORMALDEHYDE; HEXANOIC ACID DERIVATIVE; METHYLMALONIC ACID; PROPIONAMIDE DERIVATIVE; PROPIONIC ACID; VOLATILE ORGANIC COMPOUND;

ARTICLE; CHEMICAL REACTION; CHEMICAL STRUCTURE; DECISION TREE; HIGH THROUGHPUT SCREENING; MACHINE LEARNING; PHYSICAL CHEMISTRY; PREDICTION; PRIORITY JOURNAL; QUANTITATIVE STRUCTURE ACTIVITY RELATION; RANDOM FOREST; RECEIVER OPERATING CHARACTERISTIC; SKIN SENSITIZATION; SUPPORT VECTOR MACHINE;

EID: 67649791997     PISSN: 0920654X     EISSN: 15734951     Source Type: Journal    
DOI: 10.1007/s10822-009-9275-2     Document Type: Article

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