Neural Networks in QSAR and Drug Design book cover

Neural Networks in QSAR and Drug Design

Audience
Academic and industrial scientists involved in QSAR and Drug Design which are techniques increasingly used in medicinal chemistry, pharmacology, (eco)toxicology, and agrochemistry; students taking courses in computational chemistry and chemometrics.

Hardbound, 284 pages

Published: August 1996

Imprint: Academic Press

ISBN: 978-0-12-213815-7

Contents

  • J. Devillers, Preface. J. Devillers, Strengths and Weaknesses of the Backpropagation Neural Network in QSAR and QSPR Studies. D. Domine, J. Devillers, and W. Karcher, AUTOLOGP Versus Neural Network Estimationof n-Octanol/Water Partition Coefficients. J. Devillers, D. Domine, and R.S. Boethling, Use of a Backpropagation Neural Network and Autocorrelation Descriptors for Predicting the Biodegradation of Organic Chemicals. M. Chastrette and C. ElAidi, Structure-Bell-Pepper Odor Relationships for Pyrazines and Pyridines. J. Devillers, C. Guillon, and D. Domine, A Neural Structure-Odor Threshold Model for Chemicals of Environmental and Industrial Concern. D. Wienke, D. Domine, L. Buydens, and J. Devillers, Adaptive Resonance Theory Based Neural Networks Explored for Pattern Recognition Analysis of QSAR Data. D.J. Livingstone, Multivariate Data Display Using Neural Networks. D.T. Manallack, T. Gallagher, and D.J. Livingstone, Quantitative Structure-Activity Relationships of Nicotinic Agonists. S. Anzali, G. Barnickel, M. Krug, J. Sadowski, M. Wagener, and J. Gasteiger, Evaluation of Molecular Surface Properties Using a Kohonen Neural Network. D. Domine, D. Wienke,J. Devillers, and L. Buydens, A New Nonlinear Neural Mapping Technique for Visual Exploration of QSAR Data. G.M. Maggiora, C.T. Zhang, K.C. Chou, and D.W. Elrod, Combining Fuzzy Clustering and Neural Networks to Predict Protein Structural Classes. Index.

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