Effect of selection of molecular descriptors on the prediction of blood-brain barrier penetrating and nonpenetrating agents by statistical learning methods

Journal of Chemical Information and Modeling

Volumn 45, Issue 5, 2005, Pages 1376-1384

  Li, Hu ^a   Yap, Chun Wei ^a   Ung, Choong Yong ^a   Xue, Ying ^a,b   Cao, Zhi Wei ^c   Chen, Yu Zong ^a,c  

^a NATIONAL UNIVERSITY OF SINGAPORE   (Singapore)

^b SICHUAN UNIVERSITY   (China)

^c SHANGHAI CENTER FOR BIOINFORMATION TECHNOLOGY   (China)

Author keywords

[No Author keywords available]

Indexed keywords

BLOOD; BRAIN; DRUG PRODUCTS; NEUROLOGY; OPTIMIZATION; STATISTICAL METHODS;

BLOOD-BRAIN BARRIER (BBB); CENTRAL NERVOUS SYSTEM; LOGISTIC REGRESSION; MOLECULAR DESCRIPTORS;

MOLECULAR DYNAMICS;

DRUG;

ARTICLE; ARTIFICIAL INTELLIGENCE; BIOLOGY; BLOOD BRAIN BARRIER; CHEMICAL STRUCTURE; CHEMISTRY; COMPUTER SIMULATION; DRUG DESIGN; METABOLISM; METHODOLOGY; SENSITIVITY AND SPECIFICITY; STATISTICAL MODEL; STRUCTURE ACTIVITY RELATION;

ARTIFICIAL INTELLIGENCE; BLOOD-BRAIN BARRIER; COMPUTATIONAL BIOLOGY; COMPUTER SIMULATION; DRUG DESIGN; MODELS, STATISTICAL; MOLECULAR STRUCTURE; PHARMACEUTICAL PREPARATIONS; SENSITIVITY AND SPECIFICITY; STRUCTURE-ACTIVITY RELATIONSHIP;

EID: 26944502743     PISSN: 15499596     EISSN: 1549960X     Source Type: Journal    
DOI: 10.1021/ci050135u     Document Type: Article

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