Preface
1.: Barry K. Lavine and Jerome Workman, Jr.: Chemometrics: Past, Present, and Future
2.: Steven D. Brown, HuWei Tan, and Robert Feudale: Improving the Robustness of Multivariate Calibrations
3.: Fredrik Pettersson and Anders Berglund: Interpretation and Validation of PLS Models for Microarray Data
4.: Ling Xue, Florence L. Stahura, and Jurgen Bajorath: Chemoinformatics: Perspectives and Challenges
5.: G. W. A. Milne: Mathematics as a Basis for Chemistry
6.: John D. Holliday, Naomie Salim, and Peter Willett: On the Magnitudes of Coefficient Values in the Calculation of Chemical Similarity and Dissimilarity
7.: Rajni Garg: Chemoinformatics and Comparative Quantitative Structure-Activity Relationship
8.: Curt M. Breneman, Minghu Song, Jinbo Bi, N. Sukumar, Kristin P. Bennett, Steven Cramer, and N. Tugcu: Prediction of Protein Retention Times in Anion-Exchange Chromatography Systems Using Support Vector Regression
9.: Barry K. Lavine, Charles E. Davidson, Curt Breneman, and William Katt: Analysis of Odor Structure Relationships Using Electonic Van Der Waals Surface Property Descriptors and Genetic Algorithms
10.: Douglas R. Henry and Joseph L. Durant, Jr.: Optimization of MDL Substructure Search Keys for the Prediction of Activity and Toxicity
11.: Norah E. MacCuish and John D. MacCuish: Clustering Compound Data: Asymetric Clustering of Chemical Datasets
12.: Weida Tong, Huixiao Hong, Hong Fang, Qian Xie, Roger Perkins, and John D. Walker: From Decision Tree to Heterogeneous Decision Forest: A Novel Chemometrics Approach for Structure-Activity Relationship Modeling