In silico target predictions: Defining a benchmarking data set and comparison of performance of the multiclass Naïve Bayes and Parzen-Rosenblatt Window

Journal of Chemical Information and Modeling

Volumn 53, Issue 8, 2013, Pages 1957-1966

  Koutsoukas, Alexios ^a   Lowe, Robert ^a   Kalantarmotamedi, Yasaman ^a   Mussa, Hamse Y ^a   Klaffke, Werner ^b   Mitchell, John B O ^c   Glen, Robert C ^a   Bender, Andreas ^a  

^a UNIVERSITY OF CAMBRIDGE   (United Kingdom)

^b UNILEVER RESEARCH VLAARDINGEN   (Netherlands)

^c UNIVERSITY OF ST ANDREWS   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

BARIUM COMPOUNDS; BENCHMARKING; BIOACTIVITY; DATA MINING; FORECASTING; LEARNING ALGORITHMS; MACHINE LEARNING; PREDICTIVE ANALYTICS; PROTEINS; STATISTICAL TESTS;

BINARY CLASSIFICATION; BIOACTIVE COMPOUNDS; BIOACTIVE MOLECULES; CHEMICAL SUBSTANCE; COMPARISON OF PERFORMANCE; PERFORMANCE MEASURE; PROBABILISTIC MACHINES; STRUCTURAL SIMILARITY;

CLASSIFICATION (OF INFORMATION);

LIGAND; PROTEIN; PROTEIN BINDING;

ALGORITHM; BAYES THEOREM; BIOLOGY; COMPARATIVE STUDY; DRUG DEVELOPMENT; HUMAN; METABOLISM; PROCEDURES; QUALITY CONTROL; REPRODUCIBILITY; ARTICLE; METHODOLOGY; PROTEIN BINDING;

ALGORITHMS; BAYES THEOREM; BENCHMARKING; COMPUTATIONAL BIOLOGY; DRUG DISCOVERY; HUMANS; LIGANDS; PROTEIN BINDING; PROTEINS; REPRODUCIBILITY OF RESULTS;

EID: 84883239935     PISSN: 15499596     EISSN: 1549960X     Source Type: Journal    
DOI: 10.1021/ci300435j     Document Type: Article

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