Methods to Improve the Reliability, Validity and Interpretability
of QSAR Models.
Ph.D Thesis, Pennsylvania State University, 2005
|
|
Full document
|
|
|
|
Abstract
|
|
|
Chapter 1
|
Introduction
|
|
|
Chapter 2
|
Statistical & Optimization Techniques
|
|
|
Chapter 3
|
QSAR Methodology and ADAPT
|
|
|
Chapter 4
|
Generation of QSAR Sets Using a
Self-Organizing 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
|
|