Evaluating the performances of quantitative structure-retention relationship models with different sets of molecular descriptors and databases for high-performance liquid chromatography predictions

Journal of Chromatography A

Volumn 1216, Issue 25, 2009, Pages 5030-5038

  Wang, Chunlei ^a   Skibic, Michael J ^b   Higgs, Richard E ^b   Watson, Ian A ^b   Bui, Hai ^b   Wang, Jibo ^b   Cintron, Jose M ^b  

^a UNIVERSITY OF TEXAS AT ARLINGTON   (United States)

^b ELI LILLY AND COMPANY   (United States)

Author keywords

Database selection; Log D; Molecular descriptors; Partial least squares; Quantitative structure retention relationships; Random forests; Root mean square error of prediction

Indexed keywords

DATABASE SELECTION; LOG D; MOLECULAR DESCRIPTORS; PARTIAL LEAST SQUARES; QUANTITATIVE STRUCTURE-RETENTION RELATIONSHIPS; RANDOM FORESTS; ROOT-MEAN-SQUARE ERROR OF PREDICTION;

CHROMATOGRAPHIC ANALYSIS; CURVE FITTING; HIGH PRESSURE LIQUID CHROMATOGRAPHY; LEAST SQUARES APPROXIMATIONS; SULFUR COMPOUNDS;

DRUG PRODUCTS;

ANALYTICAL ERROR; ARTICLE; DATA BASE; HIGH PERFORMANCE LIQUID CHROMATOGRAPHY; MODEL; MOLECULAR MODEL; PREDICTION; PRIORITY JOURNAL; QUANTITATIVE STRUCTURE PROPERTY RELATION; QUANTITATIVE STRUCTURE RETENTION RELATION; VALIDATION PROCESS;

CHROMATOGRAPHY, HIGH PRESSURE LIQUID; DATABASES, FACTUAL; HYDROGEN-ION CONCENTRATION; MODELS, CHEMICAL; MODELS, STATISTICAL; PHARMACEUTICAL PREPARATIONS; QUANTITATIVE STRUCTURE-ACTIVITY RELATIONSHIP; REPRODUCIBILITY OF RESULTS;

EID: 65649121587     PISSN: 00219673     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.chroma.2009.04.064     Document Type: Article

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