Genetic Partial Least Squares in QSAR

[1]  L. Hammett,et al.  Physical organic chemistry , 1940 .

[2]  C. Hansch.  Quantitative approach to biochemical structure-activity relationships , 1969 .

[3]  John H. Holland,et al.  Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence , 1992 .

[4]  S. Wold.  Cross-Validatory Estimation of the Number of Components in Factor and Principal Components Models , 1978 .

[5]  S. Wold,et al.  The Collinearity Problem in Linear Regression. The Partial Least Squares (PLS) Approach to Generalized Inverses , 1984 .

[6]  W. Dunn,et al.  Principal components analysis and partial least squares regression , 1989 .

[7]  D. Livingstone,et al.  Structure-activity relationships of antifilarial antimycin analogues: a multivariate pattern recognition study. , 1990, Journal of medicinal chemistry.

[8]  J. Friedman.  Multivariate adaptive regression splines , 1990 .

[9]  John Wood,et al.  Single Class Discrimination Using Principal Component Analysis (SCD‐PCA) , 1991 .

[10]  David Rogers,et al.  G/SPLINES: A Hybrid of Friedman's Multivariate Adaptive Regression Splines (MARS) Algorithm with Holland's Genetic Algorithm , 1991, ICGA.

[11]  D J Livingstone,et al.  Novel method for the display of multivariate data using neural networks. , 1991, Journal of molecular graphics.

[12]  H. Macfie,et al.  An application of unsupervised neural network methodology Kohonen topology-Preserving mapping) to QSAR analysis , 1991 .

[13]  John Wood,et al.  Generalized Single Class Discrimination (GSCD). A New Method for the Analysis of Embedded Structure‐Activity Relationships , 1992 .

[14]  Variable selection in PLS analysis , 1993 .

[15]  James H. Wikel,et al.  The use of neural networks for variable selection in QSAR , 1993 .

[16]  S Forrest,et al.  Genetic algorithms , 1996, CSUR.

[17]  Hxugo Kubiny.  Variable Selection in QSAR Studies. I. An Evolutionary Algorithm , 1994 .

[18]  James W. McFarland,et al.  On Identifying Likely Determinants of Biological Activity in High Dimensional QSAR Problems , 1994 .

[19]  H. Kubinyi.  Variable Selection in QSAR Studies. II. A Highly Efficient Combination of Systematic Search and Evolution , 1994 .

[20]  Anton J. Hopfinger,et al.  Application of Genetic Function Approximation to Quantitative Structure-Activity Relationships and Quantitative Structure-Property Relationships , 1994, J. Chem. Inf. Comput. Sci..

[21]  Brian T. Luke,et al.  Evolutionary Programming Applied to the Development of Quantitative Structure-Activity Relationships and Quantitative Structure-Property Relationships , 1994, J. Chem. Inf. Comput. Sci..

[22]  Donald G. Truhlar,et al.  Parameterization of NDDO wavefunctions using genetic algorithms. An evolutionary approach to parameterizing potential energy surfaces and direct dynamics calculations for organic reactions , 1995 .