Generative Topographic Mapping (GTM): Universal tool for data visualization, structure-activity modeling and dataset comparison

Molecular Informatics

Volumn 31, Issue 3-4, 2012, Pages 301-312

  Kireeva, N ^a,b   Baskin, I I ^a,c   Gaspar, H A ^a   Horvath, D ^a   Marcou, G ^a   Varnek, A ^a  

^a UNIVERSITÉ LOUIS PASTEUR   (France)

^b FRUMKIN INSTITUTE OF PHYSICAL CHEMISTRY AND ELECTROCHEMISTRY   (Russian Federation)

^c MOSCOW STATE UNIVERSITY   (Russian Federation)

Author keywords

Bhattacharyya kernel; Comparison of databases; Data visualization; Dimensionality reduction; Generative topographic maps; Manifold learning; Predicting activity profiles

Indexed keywords

BAYESIAN NETWORKS; CONFORMAL MAPPING; DATABASE SYSTEMS; DISTRIBUTION FUNCTIONS; MAPS; PRINCIPAL COMPONENT ANALYSIS; PROBABILITY DENSITY FUNCTION; SELF ORGANIZING MAPS; VISUALIZATION;

ACTIVITY MODELING; ACTIVITY PROFILE; BHATTACHARYYUM KERNEL; COMPARISON OF DATABASE; DIMENSIONALITY REDUCTION; GENERATIVE TOPOGRAPHIC MAP; GENERATIVE TOPOGRAPHIC MAPPING; MANIFOLD LEARNING; PREDICTING ACTIVITY PROFILE; STRUCTURE ACTIVITY;

DATA VISUALIZATION;

ARTICLE; BAYES THEOREM; DATA ANALYSIS; DATA BASE; DENSITY FUNCTIONAL THEORY; KERNEL METHOD; PRIORITY JOURNAL; STRUCTURE ACTIVITY RELATION;

EID: 84859890850     PISSN: 18681743     EISSN: 18681751     Source Type: Journal    
DOI: 10.1002/minf.201100163     Document Type: Article

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