Prediction of PKCθ inhibitory activity using the random forest algorithm

International Journal of Molecular Sciences

Volumn 11, Issue 9, 2010, Pages 3413-3433

  Hao, Ming ^a   Li, Yan ^a   Wang, Yonghua ^b   Zhang, Shuwei ^a  

^a DALIAN UNIVERSITY OF TECHNOLOGY   (China)

^b NORTHWEST A F UNIVERSITY   (China)

Author keywords

Partial Least Square; Protein kinase C ; Random Forest; Support Vector Machine

Indexed keywords

NITROGEN; OXYGEN; PROTEIN KINASE C INHIBITOR; PROTEIN KINASE C THETA INHIBITOR; UNCLASSIFIED DRUG;

ALGORITHM; ARTICLE; CONTROLLED STUDY; ENZYME ACTIVITY; ENZYME INHIBITION; HYDROGEN BOND; IC 50; PARTIAL LEAST SQUARES REGRESSION; PREDICTION; QUANTITATIVE STRUCTURE ACTIVITY RELATION; RANDOM FOREST; SCREENING; SUPPORT VECTOR MACHINE;

PARTIAL LEAST SQUARE; PROTEIN KINASE C Θ; RANDOM FOREST; SUPPORT VECTOR MACHINE;

ALGORITHMS; HUMANS; ISOENZYMES; PROTEIN KINASE C; PROTEIN KINASE INHIBITORS; QUANTITATIVE STRUCTURE-ACTIVITY RELATIONSHIP;

EID: 77958475350     PISSN: None     EISSN: 14220067     Source Type: Journal    
DOI: 10.3390/ijms11093413     Document Type: Article

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