Data Analysis for Chemists -
QSAR & Chemical Product Design

D. J. Livingstone

Contents List:

Chapter 1 Chemical properties and chemical structure

1.1 Introduction

1.2 What is QSAR/QSPR?

1.3 Why look for quantitative relationships?

1.4 Sources of data

1.4.1 Dependent data

1.4.2 Independent data

1.5 Analytical methods
References 

Chapter 2 Experimental Design - Compound & Parameter Selection

2.1 What is experimental design?

2.2 Experimental design techniques

2.2.1 Single-factor design methods

2.2.2 Factorial design (multiple-factor design)

2.2.3 D-optimal design

2.3 Strategies for compound selection

2.4 Summary

References

Chapter 3 Data Pre-treatment

3.1 Introduction

3.2 The Nature of Data

3.3 Data Distribution

3.4 Scaling

3.5 Data reduction

3.6 Summary

References

Chapter 4 Data Display

4.1 Introduction

4.2 Linear methods

4.3 Non-linear methods

4.4 Summary

References

Chapter 5 Unsupervised Learning

5.1 Introduction

5.2 Nearest-neighbour methods

5.3 Factor analysis

5.4 Cluster analysis

5.5 Cluster Significance analysis

5.6 Summary

References

Chapter 6 Regression analysis

6.1 Introduction

6.2 Simple linear regression

6.3 Multiple linear regression

6.3.1 Creating multiple regression models

6.3.2 Non-linear regression models

6.3.3 Regression with indicator variables

6.4 Multiple regression 

6.4.1.Robustness (cross-validation)

6.4.2 Chance effects

6.4.3 Comparison of regression models

6.5 Summary

References

Chapter 7 Supervised Learning

7.1 Introduction

7.2 Discriminant techniques

7.2.1 Discriminant analysis

7.2.2 SIMCA

7.2.3 Conditions & Cautions for Discriminant Analysis

7.3 Regression on principal Components & PLS

7.3.1 Regression on Principal Components

7.3.2 PLS

7.3.3 Continuum Regression

7.4 Feature Selection.

7.5 Summary

References

Chapter 8 Treatment of multiple Dependent variables

8.1 Introduction

8.2 Principal Components and Factor Analysis

8.3 Cluster Analysis

8.4 Spectral Map Analysis

8.5 Regression Models with Multiple Dependent Data

8.6 Summary

References

Chapter 9 Artificial Intelligence

9.1 Introduction

9.2 Expert Systems

9.2.1 LogP Prediction

9.2.2 Toxicity Prediction

9.2.3 Reaction and Structure Prediction

9.3 Neural Networks

9.3.1 Data Display

9.3.2 Statistics

9.4 Miscellaneous AI techniques

9.5 Summary

References