Editors:
- Includes cutting-edge methods and protocols
- Provides step-by-step detail essential for reproducible results
- Contains key notes and implementation advice from the experts?
Part of the book series: Methods in Molecular Biology (MIMB, volume 2190)
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Table of contents (17 protocols)
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Front Matter
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Back Matter
About this book
This volume presents examples of how Artificial Neural Networks (ANNs) are applied in biological sciences and related areas. Chapters cover a wide variety of topics, including the analysis of intracellular sorting information, prediction of the behavior of bacterial communities, biometric authentication, studies of Tuberculosis, gene signatures in breast cancer classification, the use of mass spectrometry in metabolite identification, visual navigation, and computer diagnosis. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, application details for both the expert and non-expert reader, and tips on troubleshooting and avoiding known pitfalls.
Authoritative and practical, Artificial Neural Networks: Third Edition should be of value to all scientists interested in the hands-on application of ANNs in the biosciences.
Editors and Affiliations
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Chemistry, Oxford University, Oxford, UK
Hugh Cartwright
Bibliographic Information
Book Title: Artificial Neural Networks
Editors: Hugh Cartwright
Series Title: Methods in Molecular Biology
DOI: https://doi.org/10.1007/978-1-0716-0826-5
Publisher: Humana New York, NY
eBook Packages: Springer Protocols
Copyright Information: Springer Science+Business Media, LLC, part of Springer Nature 2021
Hardcover ISBN: 978-1-0716-0825-8Published: 18 August 2020
Softcover ISBN: 978-1-0716-0828-9Published: 18 August 2021
eBook ISBN: 978-1-0716-0826-5Published: 17 August 2020
Series ISSN: 1064-3745
Series E-ISSN: 1940-6029
Edition Number: 3
Number of Pages: XII, 359
Number of Illustrations: 20 b/w illustrations, 114 illustrations in colour
Topics: Neurosciences