Finding Chemical Structures Corresponding to a Set of Coordinates in Chemical Descriptor Space

Molecular Informatics

Volumn 36, Issue 8, 2017, Pages

  Miyao, Tomoyuki ^a   Funatsu, Kimito ^a  

^a UNIVERSITY OF TOKYO   (Japan)

Author keywords

chemical structure existence; inverse QSPR QSAR; machine learning

Indexed keywords

INVERSE PROBLEMS; LEARNING SYSTEMS; MACHINE LEARNING;

CHEMICAL DESCRIPTORS; CHEMICAL SPACE; CHEMICAL STRUCTURE EXISTENCE; DATA DOMAINS; DESCRIPTORS; DOMAIN FEATURE; INVERSE QSPR/QSAR; MACHINE-LEARNING; TRAINING DATA; TRAINING DATASET;

STRUCTURE (COMPOSITION);

ARTICLE; CHEMICAL STRUCTURE; GAUSSIAN MIXTURE MODEL; KERNEL METHOD; ONE CLASS SUPPORT VECTOR MACHINE; PRIORITY JOURNAL; QUANTITATIVE STRUCTURE ACTIVITY RELATION; QUANTITATIVE STRUCTURE PROPERTY RELATION; SUPPORT VECTOR MACHINE; ALGORITHM; CHEMICAL MODEL; CHEMISTRY; DRUG DESIGN; SOFTWARE; SOLUBILITY;

CARBON;

ALGORITHMS; CARBON; DRUG DESIGN; MODELS, CHEMICAL; MOLECULAR STRUCTURE; QUANTITATIVE STRUCTURE-ACTIVITY RELATIONSHIP; SOFTWARE; SOLUBILITY; SUPPORT VECTOR MACHINE;

EID: 85018582391     PISSN: 18681743     EISSN: 18681751     Source Type: Journal    
DOI: 10.1002/minf.201700030     Document Type: Article

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