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Neural networks in QSAR and drug design

Author: James Devillers
Publisher: London ; San Diego : Harcourt Brace, ©1996.
Series: Principles of QSAR and drug design.
Edition/Format:   eBook : Document : EnglishView all editions and formats
Database:WorldCat
Summary:
Comprehensive and impeccably edited, Neural Networks in QSAR and Drug Design is the first book to present an all-inclusive coverage of the topic. The book provides a practice-oriented introduction to the different neural network paradigms, allowing the reader to easily understand and reproduce the results demonstrated. Numerous examples are detailed, demonstrating a variety of applications to QSAR and drug design.  Read more...
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Genre/Form: Electronic books
Additional Physical Format: Print version:
Neural networks in QSAR and drug design.
London ; San Diego : Harcourt Brace, ©1996
(OCoLC)35759413
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: James Devillers
ISBN: 9780122138157 0122138155 9780080537382 0080537383
OCLC Number: 162571780
Description: 1 online resource (x, 284 pages, 11 pages of plates) : illustrations (some color).
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.
Series Title: Principles of QSAR and drug design.
Responsibility: edited by James Devillers.

Abstract:

This text provides a practice-oriented introduction to different neural network paradigms, to allow the reader to understand and reproduce the results demonstrated. Numerous examples are detailed,  Read more...

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