Application of random forest and multiple linear regression techniques to QSPR prediction of an aqueous solubility for military compounds

Molecular Informatics

Volumn 29, Issue 5, 2010, Pages 394-406

  Kovdienko, Nikolay A ^a   Polishchuk, Pavel G ^b   Muratov, Eugene N ^b,c   Artemenko, Anatoly G ^b   Kuz'min, Victor E ^b   Gorb, Leonid ^d   Hill, Frances ^e   Leszczynski, Jerzy ^a,e  

^a JACKSON STATE UNIVERSITY   (United States)

^b A V BOGATSKY PHYSICO CHEMICAL INSTITUTE   (Ukraine)

^c University of North Carolina   (United States)

^d SpecPro Inc ^*  (United States)

^e US ARMY ENGINEER RESEARCH AND DEVELOPMENT CENTER   (United States)

Author keywords

Environmental chemistry; Structure property relationships

Indexed keywords

FORESTRY; MOLECULAR STRUCTURE; ORGANIC COMPOUNDS; SOLUBILITY;

AQUEOUS SOLUBILITY; ENVIRONMENTAL CHEMISTRY; LINEAR REGRESSION TECHNIQUES; MULTIPLE LINEAR REGRESSIONS; RANDOM FOREST METHODS; RANDOM FORESTS; REGRESSION FORESTS; SIMPLEX REPRESENTATION; STATISTIC MODELING; STRUCTURE-PROPERTIES RELATIONSHIPS;

MULTIPLE LINEAR REGRESSION;

ORGANIC COMPOUND;

ACCURACY; AQUEOUS SOLUTION; ARTICLE; BIOINFORMATICS; CHEMICAL ANALYSIS; CHEMICAL STRUCTURE; CHIRALITY; DEGRADATION; DISSOLUTION; HYDROGEN BOND; HYDROPHOBICITY; MULTIPLE LINEAR REGRESSION ANALYSIS; PHYSICAL CHEMISTRY; PREDICTION; PRIORITY JOURNAL; QUANTITATIVE STRUCTURE PROPERTY RELATION; RANDOM FOREST; SOLUBILITY;

EID: 77952703658     PISSN: 18681743     EISSN: 18681751     Source Type: Journal    
DOI: 10.1002/minf.201000001     Document Type: Article

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