QSPR models for predicting log pliver values for volatile organic compounds combining statistical methods and domain knowledge

Molecules

Volumn 17, Issue 12, 2012, Pages 14937-14953

  Palomba, Damiän ^a,b   Martïnez, Marïa J ^b   Ponzoni, Ignacio ^a,b   Dïaz, Mönica F ^a,b   Vazquez, Gustavo E ^b   Soto, Axel J ^c  

^a PLAPIQUI UNS CONICET   (Argentina)

^b UNIVERSIDAD NACIONAL DEL SUR   (Argentina)

^c DALHOUSIE UNIVERSITY   (Canada)

Author keywords

Log Pliver; Machine learning; QSPR; VOCs

Indexed keywords

VOLATILE ORGANIC COMPOUND;

ANIMAL; ARTICLE; ARTIFICIAL INTELLIGENCE; CHEMISTRY; DRUG EFFECT; GAS; HUMAN; LIVER; QUANTITATIVE STRUCTURE ACTIVITY RELATION; RAT; THEORETICAL MODEL;

ANIMALS; ARTIFICIAL INTELLIGENCE; GASES; HUMANS; LIVER; MODELS, THEORETICAL; QUANTITATIVE STRUCTURE-ACTIVITY RELATIONSHIP; RATS; VOLATILE ORGANIC COMPOUNDS;

EID: 84871579816     PISSN: None     EISSN: 14203049     Source Type: Journal    
DOI: 10.3390/molecules171214937     Document Type: Article

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