The use of Bayesian nonlinear regression techniques for the modelling of the retention behaviour of volatile components of Artemisia species

References

• Bro , R . 2003 . Multivariate calibration: What is in chemometrics for the analytical chemist? . Anal. Chim. Acta. , 500 : 185 – 194 .
   Web of Science ®Google Scholar
• Borosy , AP , Keserú , K and Mátyus , P . 2000 . Application of nonlinear and local modeling methods for 3D QSAR study of class I antiarrhythmics . Chemom. Intell. Lab. Syst. , 54 : 107 – 122 .
   Web of Science ®Google Scholar
• Kärnä , T , Corona , F and Lendasse , A . 2008 . Gaussian basis functions for chemometrics . J. Chemom. , 22 : 701 – 707 .
   Web of Science ®Google Scholar
• Wold , S , Trygg , J , Berglund , A and Antti , H . 2001 . Some recent developments in PLS modeling . Chemom. Intell. Lab. Syst. , 58 : 131 – 150 .
   Web of Science ®Google Scholar
• Zhang , MH , Xu , QS and Massart , DL . 2003 . Robust principal components regression based on principal sensitivity vectors . Chemom. Intell. Lab. Syst. , 67 : 175 – 185 .
   Web of Science ®Google Scholar
• Friedman , JH . 1991 . Multivariate adaptive regression splines . Ann. Stat. , 19 : 1 – 141 .
   Web of Science ®Google Scholar
• Walczak , B and Massart , DL . 2000 . Local modelling with radial basis function networks . Chemom. Intell. Lab. Syst. , 50 : 179 – 198 . Erratum in: B. Walczak, D.L. Massart, Chemom. Intell. Lab. Syst. 51 (2000), pp. 219–238
   Web of Science ®Google Scholar
• Cleveland , WS and Devlin , SJ . 1988 . Locally weighted regression: An approach to regression analysis by local fitting . J. Am. Stat. Assoc. , 83 : 596 – 610 .
   Web of Science ®Google Scholar
• Rogers , D and Hopfinger , AJ . 1994 . Application of genetic function approximation to quantitative structure–activity relationships and quantitative structure–property relationships . J. Chem. Inf. Comput. Sci. , 34 : 854 – 866 .
   Google Scholar
• Zhou , Y and Leung , H . 2007 . Predicting object-oriented software maintainability using multivariate adaptive regression splines . J. Syst. Software , 80 : 1349 – 1361 .
   Web of Science ®Google Scholar
• Quirós , E , Felicísimo , AM and Cuartero , A . 2009 . Testing multivariate adaptive regression splines (MARS) as a method of land cover classification of TERRA-ASTER satellite images . Sensors , 9 : 9011 – 9028 .
   PubMed Web of Science ®Google Scholar
• Crino , S and Brown , DE . 2007 . Global optimization with multivariate adaptive regression splines . IEEE Syst. Man Cybern. B , 37 : 333 – 340 .
   PubMed Web of Science ®Google Scholar
• Lee , TS , Chiu , CC , Chou , YC and Lu , CJ . 2006 . Mining the customer credit using classification and regression tree and multivariate adaptive regression splines . Comput. Statist. Data Anal. , 50 : 1113 – 1130 .
   Web of Science ®Google Scholar
• Zakeri , IF , Adolph , AL , Puyau , MR , Vohra , FA and Butte , NF . 2010 . Multivariate adaptive regression splines models for the prediction of energy expenditure in children and adolescents . J. Appl. Physiol. , 108 : 128 – 136 .
   PubMed Web of Science ®Google Scholar
• Nguyen-Cong , V , Van Dang , G and Rode , BM . 1996 . Using multivariate adaptive regression splines to QSAR studies of dihydroartemisinin derivatives . Eur. J. Med. Chem. , 31 : 797 – 803 .
   PubMed Web of Science ®Google Scholar
• Fan , Y , Shi , LM , Kohn , KW , Pommier , Y and Weinstein , JN . 2001 . Quantitative structure–antitumor activity relationships of camptothecin analogues: Cluster analysis and genetic algorithm-based studies . J. Med. Chem. , 44 : 3254 – 3263 .
   PubMed Web of Science ®Google Scholar
• Xu , QS , Massart , DL , Liang , YZ and Fang , KT . 2003 . Two-step multivariate adaptive regression splines for modeling a quantitative relationship between gas chromatography retention indices and molecular descriptors . J. Chromatogr. A. , 998 : 155 – 167 .
   PubMed Web of Science ®Google Scholar
• Powell , MJD . 1987 . “ Radial basis functions for multivariable interpolation: A review ” . In Algorithms for Approximation , Edited by: Mason , JC and Cox , MG . 143 – 167 . Oxford : Clarendon Press .
   Google Scholar
• Sheta , AF and Jong , KD . 2001 . Time-series forecasting using GA-tuned radial basis function . Inf. Sci. , 133 : 221 – 228 .
   Web of Science ®Google Scholar
• Denison , DGT , Mallick , BK and Smith , AFM . 1998 . Bayesian MARS . Stat. Comput. , 8 : 337 – 346 .
   Web of Science ®Google Scholar
• Holmes , CC and Denison , DGT . 2003 . Classification with Bayesian MARS . Mach. Learn. , 50 : 159 – 173 .
   Web of Science ®Google Scholar
• Denison , DGT , Holmes , CC , Mallick , BK and Smith , AFM . 2002 . Bayesian methods for nonlinear classification and regression , West Sussex , UK : Wiley Series in Probability and Statistics, John Wiley and Sons Ltd .
   Google Scholar
• Armstrong , N and Hibbert , DB . 2009 . An introduction to Bayesian methods for analyzing chemistry data: Part I: An introduction to Bayesian theory and methods . Chemom. Intell. Lab. Syst. , 97 : 194 – 210 .
   Web of Science ®Google Scholar
• Hibbert , DB and Armstrong , N . 2009 . An introduction to Bayesian methods for analyzing chemistry data: Part II: A review of applications of Bayesian methods in chemistry . Chemom. Intell. Lab. Syst. , 97 : 211 – 220 .
   Web of Science ®Google Scholar
• Moussaoui , S , Carteret , C , Brie , D and Mohammad-Djafari , A . 2006 . Bayesian analysis of spectral mixture data using Markov Chain Monte Carlo Methods . Chemom. Intell. Lab. Syst. , 81 : 137 – 148 .
   Web of Science ®Google Scholar
• Deconinck , E , Coomans , D and Vander Heyden , Y . 2007 . Exploration of linear modelling techniques and their combination with multivariate adaptive regression splines to predict gastro-intestinal absorption of drugs . J. Pharm. Biomed. Anal. , 43 : 119 – 130 .
   PubMed Web of Science ®Google Scholar
• Jalali-Heravi , M , Asadollahi-Baboli , M and Mani-Varnosfaderani , A . 2009 . Shuffling multivariate adaptive regression splines and adaptive neuro-fuzzy inference system as tools for QSAR study of SARS inhibitors . J. Pharm. Biomed. Anal. , 50 : 853 – 860 .
   PubMed Web of Science ®Google Scholar
• Brown , PJ , Vannucci , M and Fearn , T . 2002 . Bayes model averaging with selection of regressors . J. R. Stat. Soc. Ser. B Stat. Methodol. , 64 : 519 – 536 .
   Web of Science ®Google Scholar
• Brown , PJ , Vannucci , M and Fearn , T . 1998 . Multivariate Bayesian variable selection and prediction . J. R. Stat. Soc. Ser. B Stat. Methodol. , 60 : 627 – 641 .
   Web of Science ®Google Scholar
• Brown , PJ , Vannucci , M and Fearn , T . 1998 . Bayesian wavelength selection in multicomponent analysis . J. Chemometr. , 12 : 173 – 182 .
   Web of Science ®Google Scholar
• Rasmussen , CE and Williams , CKI . 2006 . Gaussian Processes for Machine Learning , Cambridge , MA : The MIT Press .
   Google Scholar
• Costa , R , De Fina , MR , Valentino , MR , Rustaiyan , A , Dugo , P , Dugo , G and Mondello , L . 2009 . An investigation on the volatile composition of some Artemisia species from Iran . Flavour Frag. J. , 24 : 75 – 82 .
   Web of Science ®Google Scholar
• Hyperchem, Molecular Modelling System, Hyper Cube, Inc. Gainesville, Florida, USA, 1993, developed by Hyper Cube, Inc
   Google Scholar
• Todeschini , R , Consonni , V , Mauri , A and Pavan , M . Software Dragon: Calculation of Molecular Descriptors, Department of Environmental Sciences, University of Milano-Bicocca and Talete, srl. Milan, Italy, 2003; software available at www.talete.mi.it/products/dragon_description.htm
   Google Scholar
• Kohonen , T . Self-Organization and Associative Memory, Springer Series in Information Sciences, Vol. 8, Springer, Berlin, 1988
   Google Scholar
• Jalali-Heravi , M and Mani-Varnosfaderani , A . 2011 . QSAR modelling of integrin antagonists using enhanced Bayesian regularised genetic neural networks . SAR QSAR Environ. Res. , 22 : 293 – 314 .
   PubMed Web of Science ®Google Scholar
• Leardi , R and Lupiáñez González , A . 1998 . Genetic algorithms applied to feature selection in PLS regression: How and when to use them . Chemometr. Intell. Lab. Syst. , 41 : 195 – 207 .
   Web of Science ®Google Scholar
• Araújo , MCU , Bezerra Saldanha , TC , Galvão , RKH , Yoneyama , T , Caldas Chame , H and Visani , V . 2001 . The successive projections algorithm for variable selection in spectroscopic multicomponent analysis . Chemom. Intell. Lab. Syst. , 57 : 65 – 73 .
   Web of Science ®Google Scholar
• Galvão , RK and Araújo , MCU . 2009 . Variable selection. Vol. 3, S.D. Brown, R. Tauler, and B. Walczak, eds., Elsevier B.V., in Comprehensive Chemometrics: Chemical and Biochemical Data Analysis Amsterdam Chapter 3.05, pp. 233–283
   Google Scholar
• MATLAB 7.4, software available at http://www.mathworks.com/products/matlab (accessed 2011)
   Google Scholar
• MATLAB code available at http://www.stats.ox.ac.uk/~cholmes/BookCode/ (accessed 2011)
   Google Scholar
• Todeschini , R and Consonni , V . 2000 . Handbook of Molecular Descriptors, Methods and Principles in Medicinal Chemistry , Weinheim : Wiley-VCH .
   Google Scholar
• Consonni , V , Todeschini , R and Pavan , M . 2002 . Structure/response correlations and similarity/diversity analysis by GETAWAY descriptors. 1. Theory of the novel 3D molecular descriptors . J. Chem. Inf. Comput. Sci. , 42 : 682 – 692 .
   PubMedGoogle Scholar
• Caballero , J , Fernández , M , Saavedra , M and González-Nilo , FD . 2008 . 2D Autocorrelation CoMFA, and CoMSIA modeling of protein tyrosine kinases’ inhibition by substituted pyrido [2,3-d]pyrimidine derivatives . Bioorg. Med. Chem. , 16 : 810 – 821 .
   PubMed Web of Science ®Google Scholar
• Ding , G , Chen , J , Qiao , X , Huang , L , Lin , J and Chen , X . 2006 . Quantitative relationships between molecular structures, environmental temperatures and solid vapor pressures of PCDD/Fs . Chemosphere , 62 : 1057 – 1063 .
   PubMed Web of Science ®Google Scholar
• Jalali-Heravi , M and Asadollahi-Baboli , M . 2008 . QSAR analysis of platelet-derived growth inhibitors using GA-ANN and shuffling cross-validation . QSAR Comb. Sci. , 27 : 750 – 757 .
   Google Scholar
• Blagojevic , P , Radulovic , N , Palic , R and Stajanovic , G . 2006 . Chemical composition of the essential oils of Serbian wild-growing Artemisia absinthium and Artemisia vulgaris . J. Agric. Food. Chem. , 54 : 4780 – 4789 .
   PubMed Web of Science ®Google Scholar
• Hashemi , P , Abolghasemi , MM , Fakhari , AR , Ebrahimi , SN and Ahmadi , S . 2007 . Hydrodistillation-solvent microextraction and GC-MS identification of volatile components of Artemisia aucheri . Chromatographia , 66 : 283 – 286 .
   Web of Science ®Google Scholar