Modified tabu search approach for variable selection in quantitative structure-activity relationship studies of toxicity of aromatic compounds

Artificial Intelligence in Medicine

Volumn 49, Issue 1, 2010, Pages 61-66

  Shen, Qi ^a   Shi, Wei Min ^a   Kong, Wei ^a  

^a ZHENGZHOU UNIVERSITY   (China)

Author keywords

Aromatic compound; Quantitative structure activity relationship; Tabu search; Variable selection

Indexed keywords

ANALYSIS SYSTEM; BEST POSITION; CANDIDATE SOLUTION; CONVERGENCE SPEED; FITNESS FUNCTIONS; INITIAL SOLUTION; LOCAL MINIMUMS; MEMORY SYSTEMS; MODIFIED CP STATISTIC; OPTIMAL POSITION; QSAR MODELING; QUANTITATIVE STRUCTURE ACTIVITY RELATIONSHIP; QUANTITATIVE STRUCTURE-ACTIVITY RELATIONSHIP STUDIES; QUANTITATIVE STRUCTURE-ACTIVITY RELATIONSHIPS; SEARCH SPACES; STEPWISE REGRESSION; VARIABLE SELECTION;

AROMATIC COMPOUNDS; AROMATIZATION; DYES; FUNCTION EVALUATION; ORGANIC CHEMICALS; SULFUR COMPOUNDS; TOXICITY;

TABU SEARCH;

AROMATIC COMPOUND;

ALGORITHM; ARTICLE; CALCULATION; CONTROLLED STUDY; INTERMETHOD COMPARISON; MATHEMATICAL MODEL; MATHEMATICAL VARIABLE; PREDICTION; PRIORITY JOURNAL; QUANTITATIVE STRUCTURE ACTIVITY RELATION; SEARCH ENGINE; STRUCTURE ANALYSIS; TABU SEARCH; TOXICITY;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; HUMANS; HYDROCARBONS, AROMATIC; MOLECULAR STRUCTURE; QUANTITATIVE STRUCTURE-ACTIVITY RELATIONSHIP; TOXICITY TESTS;

EID: 77951645950     PISSN: 09333657     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.artmed.2010.01.004     Document Type: Article

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