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Neural networks in QSAR and drug design /

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 r...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Otros Autores: Devillers, James, 1956-
Formato: Electrónico eBook
Idioma:Inglés
Publicado: London ; San Diego : Harcourt Brace, �1996.
Colección:Principles of QSAR and drug design.
Temas:
Acceso en línea:Texto completo

MARC

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245 0 0 |a Neural networks in QSAR and drug design /  |c edited by James Devillers. 
260 |a London ;  |a San Diego :  |b Harcourt Brace,  |c �1996. 
300 |a 1 online resource (x, 284 pages, 11 pages of plates) :  |b illustrations (some color) 
336 |a text  |b txt  |2 rdacontent 
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490 1 |a Principles of QSAR and drug design 
520 |a 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. The contributors include some of the most distinguished names in the field, and the book provides an exhaustive bibliography, guiding readers to all the literature related to a particular type of application or neural network paradigm. The extensive index acts as a guide to the book, and makes retrieving information from chapters an easy task. A further research aid is a list of software with indications of availablility and price, as well as the editors scale rating the ease of use and interest/price ratio of each software package. The presentation of new, powerful tools for modeling molecular properties and the inclusion of many important neural network paradigms, coupled with extensive reference aids, makes Neural Networks in QSAR and Drug Design an essential reference source for those on the frontiers of this field. Key Features * Presents the first coverage of neural networks in QSAR and Drug Design * Allows easy understanding and reproduction of the results described within * Includes an exhaustive bibliography with more than 200 references * Provides a list of applicable software packages with availability and price. 
505 0 |a 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. 
504 |a Includes bibliographical references and index. 
588 0 |a Print version record. 
546 |a English. 
650 0 |a Drugs  |x Design. 
650 0 |a Neural networks (Computer science) 
650 0 |a QSAR (Biochemistry) 
650 0 |a Drugs  |x Structure-activity relationships. 
650 0 |a Drugs. 
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650 0 2 |a Pharmaceutical Preparations  |0 (DNLM)D004364 
650 0 2 |a Neural Networks, Computer  |0 (DNLM)D016571 
650 2 |a Quantitative Structure-Activity Relationship  |0 (DNLM)D021281 
650 6 |a M�edicaments  |x Conception.  |0 (CaQQLa)201-0203461 
650 6 |a R�eseaux neuronaux (Informatique)  |0 (CaQQLa)201-0209597 
650 6 |a Relations structure-activit�e quantitatives (Biochimie)  |0 (CaQQLa)201-0379113 
650 6 |a M�edicaments  |x Relations structure-activit�e.  |0 (CaQQLa)201-0028672 
650 6 |a M�edicaments.  |0 (CaQQLa)201-0002990 
650 7 |a MEDICAL  |x Drug Guides.  |2 bisacsh 
650 7 |a MEDICAL  |x Pharmacology.  |2 bisacsh 
650 7 |a MEDICAL  |x Pharmacy.  |2 bisacsh 
650 7 |a MEDICAL  |x Nursing  |x Pharmacology.  |2 bisacsh 
650 7 |a Drugs  |2 fast  |0 (OCoLC)fst00898761 
650 7 |a Drugs  |x Design  |2 fast  |0 (OCoLC)fst00898790 
650 7 |a Drugs  |x Structure-activity relationships  |2 fast  |0 (OCoLC)fst00898929 
650 7 |a Neural networks (Computer science)  |2 fast  |0 (OCoLC)fst01036260 
650 7 |a QSAR (Biochemistry)  |2 fast  |0 (OCoLC)fst01084801 
655 2 |a Electronic information resources 
700 1 |a Devillers, James,  |d 1956- 
776 0 8 |i Print version:  |t Neural networks in QSAR and drug design.  |d London ; San Diego : Harcourt Brace, �1996  |z 0122138155  |z 9780122138157  |w (OCoLC)35759413 
830 0 |a Principles of QSAR and drug design. 
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