Probabilistic modeling of conformational space for 3D machine learning approaches

Molecular Informatics

Volumn 29, Issue 5, 2010, Pages 441-455

  Jahn, Andreas ^a   Hinselmann, Georg ^a   Fechner, Nikolas ^a   Henneges, Carsten ^a   Zell, Andreas ^a  

^a UNIVERSITY OF TÜBINGEN   (Germany)

Author keywords

4D QSAR; Flexible atom pair kernel; Gaussian mixture model; Machine learning; Molecular similarity; Probabilistic conformational space encoding

Indexed keywords

COMPUTATIONAL CHEMISTRY; CONFORMATIONS; ENCODING (SYMBOLS); FUNCTION EVALUATION; GAUSSIAN DISTRIBUTION; LEARNING SYSTEMS; MOLECULAR GRAPHICS; SIGNAL ENCODING;

4D-QSAR; CONFORMATIONAL SPACE; FLEXIBLE ATOM-PAIR KERNEL; GAUSSIAN MIXTURE MODEL; KERNEL FUNCTION; MACHINE-LEARNING; MOLECULAR SIMILARITY; PROBABILISTIC CONFORMATIONAL SPACE ENCODING; PROBABILISTICS; SPACE-ENCODING;

MOLECULES;

ARTICLE; COMPARATIVE MOLECULAR SIMILARITY INDICES ANALYSIS; CONFORMATION; KERNEL METHOD; MACHINE LEARNING; MATHEMATICAL ANALYSIS; MATHEMATICAL MODEL; PHARMACOPHORE; PRIORITY JOURNAL; PROBABILITY; SUPPORT VECTOR MACHINE;

EID: 77952678953     PISSN: 18681743     EISSN: 18681751     Source Type: Journal    
DOI: 10.1002/minf.201000036     Document Type: Article

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