Artificial neural networks : methods and applications / David J. Livingstone, editor.

Contributor(s): Livingstone, D. (David)
Material type: TextTextSeries: Methods in molecular biology (Clifton, N.J.): v. 458.Publisher: Totowa, NJ : Humana Press, ©2008Description: 1 online resource (ix, 254 pages) : illustrationsContent type: text Media type: computer Carrier type: online resourceISBN: 9781588297181; 1588297187; 9781603271011; 1603271015Subject(s): Neural networks (Computer science) | Neural Networks, Computer | Réseau neuronal (informatique) | Neural networks (Computer science) | Réseaux neuronaux (informatique)Genre/Form: Electronic books. Additional physical formats: Print version:: Artificial neural networks.DDC classification: 006.3/2 LOC classification: QA76.87 | .A7435 2008Online resources: Click here to access online
Contents:
Artificial neural networks in biology and chemistry : the evolution of a new analytical tool / Hugh M. Cartwright -- Overview of artificial neural networks / Jinming Zou, Yi Han, and Sung-Sau So -- Bayesian regularization of neural networks / Frank Burden and Dave Winkler -- Kohonen and counterpropagation neural networks applied for mapping and interpretation of IR spectra / Marjana Novic -- Artificial neural network modeling in environmental toxicology / James Devillers -- Neural networks in analytical chemistry / Mehdi Jalali-Heravi -- Application of artificial neural networks for decision support in medicine / Brendan Larder, Dechao Wang, and Andy Revell -- Neural networks in building QSAR models / Igor I. Baskin, Vladimir A. Palyulin, and Nikolai S. Zefirov -- Peptide bioinformatics : peptide classification using peptide machines / Zheng Rong Yang -- Associative neural network / Igor V. Tetko -- Neural networks predict protein structure and function / Marco Punta and Burkhard Rost -- The extraction of information and knowledge from trained neural networks / David J. Livingstone [and others].
Summary: 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.
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Includes bibliographical references and index.

Artificial neural networks in biology and chemistry : the evolution of a new analytical tool / Hugh M. Cartwright -- Overview of artificial neural networks / Jinming Zou, Yi Han, and Sung-Sau So -- Bayesian regularization of neural networks / Frank Burden and Dave Winkler -- Kohonen and counterpropagation neural networks applied for mapping and interpretation of IR spectra / Marjana Novic -- Artificial neural network modeling in environmental toxicology / James Devillers -- Neural networks in analytical chemistry / Mehdi Jalali-Heravi -- Application of artificial neural networks for decision support in medicine / Brendan Larder, Dechao Wang, and Andy Revell -- Neural networks in building QSAR models / Igor I. Baskin, Vladimir A. Palyulin, and Nikolai S. Zefirov -- Peptide bioinformatics : peptide classification using peptide machines / Zheng Rong Yang -- Associative neural network / Igor V. Tetko -- Neural networks predict protein structure and function / Marco Punta and Burkhard Rost -- The extraction of information and knowledge from trained neural networks / David J. Livingstone [and others].

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.

English.

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