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Neural Networks in QSAR and Drug Design
of: James Devillers
Elsevier Trade Monographs, 1996
ISBN: 9780080537382 , 284 Pages
Format: PDF
Copy protection: DRM
Front Cover
1
Neural Networks in QSAR and Drug Design
4
Copyright Page
5
Contents
6
Contributors
10
Preface
12
Chapter 1. Strengths and Weaknesses of the Backpropagation Neural Network in QSAR and QSPR Studies
14
Abstract
14
Introduction
14
Standard BNN Algorithm
16
Designing the Model
19
Selection of the Best BNN Model
28
Comparison of the Performances of a BNN Model with those Obtained with other Approaches
31
Software Availability
33
Hybrid Systems with BNN
33
Conclusion
36
Annex: Artificial Neural Networks (ANNs) on Internet
37
References
37
Chapter 2. AUTOLOGP Versus Neural Network Estimation of n-Octanol/Water Partition Coefficients
60
Abstract
60
Introduction
60
Materials and Methods
62
Results and Discussion
66
Concluding Remarks
70
References
71
Chapter 3. Use of a Backpropagation Neural Network and Autocorrelation Descriptors for Predicting the Biodegradation of Organic Chemicals
78
Abstract
78
Introduction
78
Biodegradation Data
79
Molecular Descriptors
89
Statistics
91
Modeling Results
92
References
94
Chapter 4. Structure–Bell-Pepper Odor Relationships for Pyrazines and Pyridines Using Neural Networks
96
Abstract
96
Introduction
97
Materials and Methods
98
Results and Discussion
103
Conclusion
105
References
106
Chapter 5. A Neural Structure–Odor Threshold Model for Chemicals of Environmental and Industrial Concern
110
Abstract
110
Introduction
111
Materials and Methods
112
Results and Discussion
122
Concluding Remarks
127
References
128
Chapter 6. Adaptive Resonance Theory Based Neural Networks Explored for Pattern Recognition Analysis of QSAR Data
132
Abstract
132
Introduction
133
Neuro-Physiological Basis of ART
134
Taxonomy and State-of-the-Art
135
Theory of ART-2a and FuzzyART
137
Data Preprocessing by Complement Coding
141
Quantification or Qualification?
142
Case Study I: Classification of Rose Varieties from their Headspace Analysis
143
Case Study II: Optimal Selection of Aliphatic Substituents
151
Conclusions
160
References
160
Chapter 7. Multivariate Data Display Using Neural Networks
170
Abstract
170
Introduction
170
Methods
172
Results and Discussion
180
Conclusions
186
References
187
Chapter 8. Quantitative Structure–Activity Relationships of Nicotinic Agonists
190
Abstract
190
Introduction
191
Methods
194
Results
201
Discussion
209
References
217
Chapter 9. Evaluation of Molecular Surface Properties Using a Kohonen Neural Network
222
Abstract
222
Introduction
222
Materials and Methods
223
Kohonen Network
224
Template Approach
225
From a 3D-Space to a 2D-Map
226
Clustering of the Structures by an Investigation of their Maps
228
In Search of the Bioactive Conformation, the Best Superposition, SAR
230
Conclusions
233
References
234
Chapter 10. A New Nonlinear Neural Mapping Technique for Visual Exploration of QSAR Data
236
Abstract
236
Introduction
236
Background
238
Case Study I: Analysis of Sensor Data
244
Case Study II: Optimal Test Series Design
250
Concluding Remarks
259
References
259
Chapter 11. Combining Fuzzy Clustering and Neural Networks to Predict Protein Structural Classes
268
Abstract
268
Introduction
269
Methodology
270
Results and Discussion
279
Caveats and Conclusions
288
References
290
Index
294
Color Plate Section
298
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