Genetic algorithm/Partial least squares

A demonstration of the performance of WCDs in a pharmaceutical setting can be illustrated by the development of a genetic algorithm/partial least-squares model of HIV reverse-transcriptase (HIVrt) inhibi-... [Pg.319]

Hoffman> B.> Cho> S. J.> Zheng> W.> Wyrick> S.> Nichols> D. E.> Mailman> R. B.> et al. (1999). Quantitative structure-activity relationship modeling of dopamine D(l) antagonists using comparative molecular field analysis> genetic algorithms-partial least-squares, and K nearest neighbor methods. The Journal of Medicinal Chemistry, 42, 3217. [Pg.1338]

Kohonen network Conceptual clustering Principal Component Analysis (PCA) Decision trees Partial Least Squares (PLS) Multiple Linear Regression (MLR) Counter-propagation networks Back-propagation networks Genetic algorithms (GA)... [Pg.442]

Broadhurst, D., Goodacre, R., Jones, A., Rowland, J. J., Kell, D. B. Anal. Chim. Acta 348, 1997, 71-86. Genetic algorithms as a method for variable selection in multiple Unear regression and partial least squares regression, with applications to pyrolysis mass spectrometry. [Pg.204]

Dunn III, W.J. and Rogers, D. (1996). Genetic Partial Least Squares in QSAR. In Genetic Algorithms in Molecular Modeling. Principles of QSAR and Drug Design. Vol. 1 (Devillers, J., ed.). Academic Press, London (UK), pp. 109-130. [Pg.562]

Drmn, W.J. Ill, and Rogers, D. (1996) Genetic partial least squares in QSAR, in Genetic Algorithms in... [Pg.1028]

Hasegawa K, Funatsu K. Partial least squares modeling and genetic algorithm optimization in quantitative structure-activity relationships. SAR QSAR Environ Res 2000 11 189-209. [Pg.611]

D QSAR Application of Genetic Algorithms and Partial Least Squares to Variable Selection of Topological Indices,... [Pg.387]

D. Broadhurst, R. Goodacre, A. Jones, J.J. Rowland and D.B. Kell, Genetic Algorithms as a Method for Variable Selection in Multiple Linear Regression and Partial Least Squares Regression, with Applications to Pyrolysis Mass Spectrometry, Analytica Chimica Acta, 348(1-3) (1997), 71-86. [Pg.406]

Wanchana, S., Yamashita, F., Hashida, M. QSAR analysis of the inhibition of recombinant GYP 3A4 activity by structurally diverse compounds using a genetic algorithm-combined partial least squares method, Pharm. Res. 2003,20,1401-8. [Pg.79]

Bangalore, A. S., Shaffer, R. E., Small, G. W. and Arnold, M. (1996) Genetic algorithm-based method for selecting wavelengths and model size for use with partial least squares regression. Application to near infrared spectroscopy. Analytical Chemistry, 68, 4200-12. [Pg.369]

Genetic Algorithms as a Method for Variable Selection in Multiple Linear Regression and Partial Least Squares Regression, with Applications to Pyrolysis Mass Spectrometry. [Pg.324]

K. Hasegawa and K. Funatsu, SAR QSAR Environ. Res., 11(3 ), 189-209 (2000). Partial Least-Squares Modeling and Genetic Algorithm Optimization in Quantitative Structure-Activity Relationships. [Pg.328]

Genetic function algorithms consider not only the presence or absence of a particular property in a regression equation, but also the form of the relationship between the property and biological activity. Linear, spline, Gaussian, and polynomial functions are frequently used. 7 For 3D-QSAR, the genetic partial least-squares method replaces the typical multiple regression calculation of the fitness with a PLS calculation. ... [Pg.193]

CAMD = computer-aided molecular design ES = evolutionary strategies GA = genetic algorithm GFA = genetic function approximation LOF = lack of fit LSE = least squares error MARS = multivariate adaptive regression spline PLS = partial least squares QSAR = quantitative structure-activity relationships RMSE = root mean squared error. [Pg.1115]