SCOPUS 정보 검색 플랫폼

QSAR and Combinatorial Science

Volumn 28, Issue 4, 2009, Pages 396-405

In silico prediction of androgenic and nonandrogenic compounds using random forest

(6) Li, Yan a Wang, Yonghua b Ding, Jun b Wang, Yuan b Chang, Yaqing b Zhang, Shuwei a

a DALIAN UNIVERSITY OF TECHNOLOGY (China)

b DALIAN OCEAN UNIVERSITY (China)

Author keywords

Androgen receptor; Classification; QSAR; Random forest

Indexed keywords

COMPUTATIONAL CHEMISTRY; FORECASTING; FORESTRY; LEAST SQUARES APPROXIMATIONS;

ANDROGEN RECEPTORS; CLASSIFICATION METHODS; CROSS VALIDATION; IN-SILICO; IN-SILICO MODELS; PERFORMANCE; PREDICTION ACCURACY; QUANTITATIVE STRUCTURE ACTIVITY RELATIONSHIP; RANDOM FORESTS; SILICO PREDICTION;

CLASSIFICATION (OF INFORMATION);

1 OCTEN 3 OL; 4,4' DIHYDROXY BENZOPHENONE; AMINOSALICYLIC ACID; ANADARONE; ANDROGEN; BENZOPHENONE; CHLORDANE; ESTRADIOL; M 1; METOLACHLOR; METRIBOLONE; MIBOLERONE; PHENOL DERIVATIVE; PHENOLPHTHALIN; PROCYMIDONE; UNCLASSIFIED DRUG;

ACCURACY; ARTICLE; COMPUTER MODEL; CONTROLLED STUDY; DRUG CLASSIFICATION; DRUG SCREENING; DRUG STRUCTURE; INFORMATION PROCESSING; INTERMETHOD COMPARISON; PARTIAL LEAST SQUARES REGRESSION; PREDICTION; PRIORITY JOURNAL; QUANTITATIVE STRUCTURE ACTIVITY RELATION; RANDOM FOREST; RELIABILITY; STRUCTURE ANALYSIS; VALIDATION STUDY; VIRTUAL REALITY;

EID: 66149131867 PISSN: 1611020X EISSN: 16110218 Source Type: Journal
DOI: 10.1002/qsar.200810100 Document Type: Article

Times cited : (21)

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