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Abstract


Chapter 1

Introduction


Chapter 2

Statistical & Optimization Techniques


Chapter 3

QSAR Methodology and ADAPT


Chapter 4

Generation of QSAR Sets Using a
SelfOrganizing Map


Chapter 5

Determining the Validity of a QSAR Model: A Classification Approach


Chapter 6

The Development of QSAR Models To Predict and Interpret the Biological Activity of Artemisinin Analogues


Chapter 7

The Development of Linear, Ensemble and Nonlinear Models for the
Prediction and Interpretation of the Biological Activity of a Set of
PDGFR Inhibitors


Chapter 8

Interpreting Computational Neural Network QSAR Models: A Measure of Descriptor Importance


Chapter 9

Interpreting Computational Neural Network QSAR Models: A Detailed Interpretation of the Weights and Biases


Chapter 10

Summary

