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SAR QSAR Environ Res

Title:		The use of Bayesian nonlinear regression techniques for the modelling of the retention behaviour of volatile components of Artemisia species
Author(s):		Jalali-Heravi M; Mani-Varnosfaderani A; Taherinia D; Mahmoodi MM;
Address:		"Department of Chemistry, Sharif University of Technology, Tehran, Iran"
Journal Title:		SAR QSAR Environ Res
Year:		2012
Volume:		20120328
Issue:		5-Jun
Page Number:		461 - 483
DOI:		10.1080/1062936X.2012.665083
ISSN/ISBN:		1029-046X (Electronic) 1026-776X (Linking)
Abstract:		"The main aim of this work was to assess the ability of Bayesian multivariate adaptive regression splines (BMARS) and Bayesian radial basis function (BRBF) techniques for modelling the gas chromatographic retention indices of volatile components of Artemisia species. A diverse set of molecular descriptors was calculated and used as descriptor pool for modelling the retention indices. The ability of BMARS and BRBF techniques was explored for the selection of the most relevant descriptors and proper basis functions for modelling. The results revealed that BRBF technique is more reproducible than BMARS for modelling the retention indices and can be used as a method for variable selection and modelling in quantitative structure-property relationship (QSPR) studies. It is also concluded that the Markov chain Monte Carlo (MCMC) search engine, implemented in BRBF algorithm, is a suitable method for selecting the most important features from a vast number of them. The values of correlation between the calculated retention indices and the experimental ones for the training and prediction sets (0.935 and 0.902, respectively) revealed the prediction power of the BRBF model in estimating the retention index of volatile components of Artemisia species"
Keywords:		"Artemisia/*chemistry *Bayes Theorem Chromatography, Gas/*methods Models, Chemical Multivariate Analysis Quantitative Structure-Activity Relationship Regression Analysis Volatile Organic Compounds/*chemistry;"
Notes:		"MedlineJalali-Heravi, M Mani-Varnosfaderani, A Taherinia, D Mahmoodi, M M eng Comparative Study Evaluation Study England 2012/03/29 SAR QSAR Environ Res. 2012 Jul; 23(5-6):461-83. doi: 10.1080/1062936X.2012.665083. Epub 2012 Mar 28"