Neural Networks in Chemistry and Drug Design: An Introduction / Edition 2

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This new edition of a best-seller offers a sound introduction to artificial neuronal networks--with insights into their architecture, functioning, and applications. Well organized and clearly written, it offers a wealth of useful information and invaluable practical guidance on this growing new area of chemical research.
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Editorial Reviews

Per the : This textbook's approach " an antidote to the hype which has attended neuronal networks in recent years." The crisply formatted volume covers basic concepts, one-layer and multilayer networks, with the expanded number of examples reflecting the surge in drug design applications. A particularly useful aspect of this introductory text is a walk-through of the entire process for each application: choice and organization of the data, selection of network architecture and parameters, and analysis of the results. Includes the 1992 first edition's preface, and appendices on programs, data sets, presentation material, publications, and Web tutorials. Zupan is at the National Institute of Chemistry in Ljubljana, Slovenia. Gasteiger is with the Institute of Organic Chemistry at the U. Erlangen- N<:u>rnberg in Germany. Annotation c. Book News, Inc., Portland, OR (
From the Publisher
?This book offers a sound introduction to artificial neuronal networks, with insights into their architecture, functioning, and applications, which is intended not only for chemists... The excellent quality of the contents and the presentation should ensure that it reaches a wide international readership.?(Angewandte Chemie)

?One of the most useful aspects of the book is a walk-through of the whole process for each application: experimental design, choice and organization of the data, selection of network architecture and parameters, and analysis of the results... The careful approach embodied in this book is an antidote to the hype which has attended neuronal networks in recent years.? (Journal of the American Chemical Society)

'... highly recommended ... could become a scientific bestseller ...' (Spectroscopy Europe)

?The attractive and clear presentation of this book make it recommendable to the complete novice.' (The Analyst)

?The book can be strongly recommended both for experienced chemists and beginners who want to learn neuronal networks.? (Trends in Analytical Chemistry)

?This textbook is an excellent introduction to the theory and practice of neuronal networks for all computationally oriented chemists who are interested in their chemical applications.' (Theoretica Chimica Acta)

?... I recommend this book to all libraries and research insitutions concerned with this fascinating and expanding field.? (Chemometrics and Intelligent Laboratory Systems)

?... offers a wealth of useful information and practical guidance in a burgeoning new area of chemical research.? ( Chemistry in Britain)

?While this book is a must for anyone contemplating the use of ANNs the clarity of thought in the analysis of these various problems is very exciting.? (NIR news)

?We strongly recommend it for library purchase and it will be a useful text for lecture courses.? (Chemistry & Industry)

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Product Details

  • ISBN-13: 9783527297795
  • Publisher: Wiley
  • Publication date: 10/26/1999
  • Edition description: 2ND
  • Edition number: 2
  • Pages: 400
  • Product dimensions: 8.09 (w) x 10.53 (h) x 0.80 (d)

Table of Contents

Pt. I Basic Concepts
1 Defining the Area 3
2 Neuron 9
3 Linking Neurons into Networks 39
Pt. II One-Layer Networks
4 Hopfield Network 55
5 Adaptive Bidirectional Associative Memory (ABAM) 67
6 Kohonen Network 81
Pt. III Multilayer Networks
7 Counter-Propagation 103
8 Back-Propagation of Errors 125
Pt. IV Applications
9 General Comments on Chemical Applications 157
10 Clustering of Multi-Component Analytical Data for Olive Oils 175
11 The Reactivity of Chemical Bonds and the Classification of Chemical Reactions 191
12 HPLC Optimization of Wine Analysis 211
13 Quantitative Structure-Activity Relationships 219
14 The Electrophilic Aromatic Substitution Reaction 243
15 Modeling and Optimizing a Recipe for a Paint Coating 253
16 Fault Detection and Process Control 261
17 Secondary Structure of Proteins 285
18 Infrared Spectrum-Structure Correlation 293
19 Properties of Molecular Surfaces 317
20 Libraries of Chemical Compounds 337
21 Representation of Chemical Structures 347
22 Prospects of Neural Networks for Chemical Applications 359
App. A Programs 363
App. B Data Sets 366
App. C Presentation Material 367
App. D Publications 367
App. E Tutorials 367
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