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Calculation of Substructural Analysis Weights Using a Genetic Algorithm
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DOI：10.1021/ci500540s.png)
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Abstract
En 中文
This work describes a genetic algorithm for the calculation of substructural analysis for use in ligand-based virtual screening. The algorithm is simple in concept and effective in operation, with simulated virtual screening experiments using the MDDR and WOMBAT data sets showing it to be superior to substructural analysis weights based on a naive Bayesian classifier.
Keywords:
STATISTICAL-HEURISTIC METHOD
ACTIVITY SPECTRA
DRUG DESIGN
SELECTION
PASS
SUBSTANCES
CLASSIFIER
PREDICTION
ENRICHMENT
RETRIEVAL
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