Artificial Neural Networks. Methods And Applications (Methods In Molecular Biology, Vol. 458) (Softcover)

88,13 € 84,74 €
Disponible
ISBN
9781617377389
Edición
Autores
David J. Livingstone
Editorial
Humana Press
Fecha Publicacion
19 abr. 2011
Características
N/D
ABOUT THIS BOOK As an extension of artificial intelligence research, artificial neural networks (ANN) aim to simulate intelligent behavior by mimicking the way that biological neural networks function. In Artificial Neural Networks, an international panel of experts report the history of the application of ANN to chemical and biological problems, provide a guide to network architectures, training and the extraction of rules from trained networks, and cover many cutting-edge examples of the application of ANN to chemistry and biology. In the tradition of the highly successful Methods in Molecular Biology™ series, this volume exhibits clear, easy-to-use information with many step-by-step laboratory protocols. Comprehensive and state-of-the-art, Artificial Neural Networks is an excellent guide to this accelerating technological field of study. Content Level » Professional/practitioner Keywords » ANN - Artificial intelligence - Network architecture Related subjects » Artificial Intelligence - Computer Science - Neuroscience TABLE OF CONTENTS Chapter 1. Artificial Neural Networks in Biology and Chemistry - the Evolution of a new Analytical Tool Hugh M. Cartwright Chapter 2. Overview of Artificial Neural Networks Jinming Zou, Yi Han, and Sung-Sau So Chapter 3. Bayesian Regularization of Neural Networks Frank Burden and Dave Winkler Chapter 4. Kohonen and Counter-propagation Neural Networks Applied for Mapping and Interpretation of IR Spectra Marjana Novic Chapter 5. Artificial Neural Network Modeling in Environmental Toxicology James Devillers Chapter 6. Neural Networks in Analytical Chemistry Mehdi Jalali-Heravi Chapter 7. Application of Artificial Neural Networks for Decision Support in Medicine Brendan Larder, Dechao Wang and Andy Revell Chapter 8. Neural Networks in Building QSAR Models Igor I. Baskin, Vladimir A. Palyulin, and Nikolai S. Zefirov Chapter 9. Peptide Bioinformatics- Peptide Classification Using Peptide Machines Zheng Rong Yang Chapter 10. Associative Neural Network Igor V. Tetko Chapter 11. Neural Networks Predict Protein Structure and Function Marco Punta and Burkhard Rost Chapter 12. The Extraction of Information and Knowledge from Trained Neural Networks David J. Livingstone, Antony Browne, Raymond Crichton, Brian D. Hudson, David Whitley and Martyn G. Ford
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