Skip to main content
SpringerLink
Log in

Artificial Neural Networks

  • Book
  • © 2015

Overview

Editors:
  1. Hugh Cartwright

    1. Chemistry Department, Oxford University, UK, and University of Victoria, Victoria, Canada

    View editor publications

    You can also search for this editor in PubMed   Google Scholar

  • Includes cutting-edge methods and protocols
  • Provides step-by-step detail essential for reproducible results
  • Contains key notes and implementation advice from the experts
  • Includes supplementary material: sn.pub/extras

Part of the book series: Methods in Molecular Biology (MIMB, volume 1260)

This is a preview of subscription content, log in via an institution to check access.

Access this book

Log in via an institution
eBook USD 99.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book USD 129.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book USD 199.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Other ways to access

Licence this eBook for your library

Institutional subscriptions

Table of contents (19 protocols)

  1. Front Matter

    Pages i-xi
    Download chapter PDF

  2. Introduction to the Analysis of the Intracellular Sorting Information in Protein Sequences: From Molecular Biology to Artificial Neural Networks

    • R. Claudio Aguilar
    Pages 1-16

  3. Protein Structural Information Derived from NMR Chemical Shift with the Neural Network Program TALOS-N

    • Yang Shen, Ad Bax
    Pages 17-32

  4. Predicting Bacterial Community Assemblages Using an Artificial Neural Network Approach

    • Peter Larsen, Yang Dai, Frank R. Collart
    Pages 33-43

  5. A General ANN-Based Multitasking Model for the Discovery of Potent and Safer Antibacterial Agents

    • A. Speck-Planche, M. N. D. S. Cordeiro
    Pages 45-64

  6. Use of Artificial Neural Networks in the QSAR Prediction of Physicochemical Properties and Toxicities for REACH Legislation

    • John C. Dearden, Philip H. Rowe
    Pages 65-88

  7. Artificial Neural Network for Charge Prediction in Metabolite Identification by Mass Spectrometry

    • J. H. Miller, B. T. Schrom, L. J. Kangas
    Pages 89-100

  8. Prediction of Bioactive Peptides Using Artificial Neural Networks

    • David Andreu, Marc Torrent
    Pages 101-118

  9. AutoWeka: Toward an Automated Data Mining Software for QSAR and QSPR Studies

    • Chanin Nantasenamat, Apilak Worachartcheewan, Saksiri Jamsak, Likit Preeyanon, Watshara Shoombuatong, Saw Simeon et al.
    Pages 119-147

  10. Ligand Biological Activity Predictions Using Fingerprint-Based Artificial Neural Networks (FANN-QSAR)

    • Kyaw Z. Myint, Xiang-Qun Xie
    Pages 149-164

  11. GENN: A GEneral Neural Network for Learning Tabulated Data with Examples from Protein Structure Prediction

    • Eshel Faraggi, Andrzej Kloczkowski
    Pages 165-178

  12. Modulation of Grasping Force in Prosthetic Hands Using Neural Network-Based Predictive Control

    • Cristian F. Pasluosta, Alan W. L. Chiu
    Pages 179-194

  13. Application of Artificial Neural Networks in Computer-Aided Diagnosis

    • Bei Liu
    Pages 195-204

  14. Developing a Multimodal Biometric Authentication System Using Soft Computing Methods

    • Mario Malcangi
    Pages 205-225

  15. Using Neural Networks to Understand the Information That Guides Behavior: A Case Study in Visual Navigation

    • Andrew Philippides, Paul Graham, Bart Baddeley, Philip Husbands
    Pages 227-244

  16. Jump Neural Network for Real-Time Prediction of Glucose Concentration

    • Chiara Zecchin, Andrea Facchinetti, Giovanni Sparacino, Claudio Cobelli
    Pages 245-259

  17. Preparation of Ta-O-Based Tunnel Junctions to Obtain Artificial Synapses Based on Memristive Switching

    • Stefan Niehörster, Andy Thomas
    Pages 261-267

  18. Architecture and Biological Applications of Artificial Neural Networks: A Tuberculosis Perspective

    • Jerry A. Darsey, William O. Griffin, Sravanthi Joginipelli, Venkata Kiran Melapu
    Pages 269-283

  19. Neural Networks and Fuzzy Clustering Methods for Assessing the Efficacy of Microarray Based Intrinsic Gene Signatures in Breast Cancer Classification and the Character and Relations of Identified Subtypes

    • Sandhya Samarasinghe, Amphun Chaiboonchoe
    Pages 285-317

  20. QSAR/QSPR as an Application of Artificial Neural Networks

    • Narelle Montañez-Godínez, Aracely C. Martínez-Olguín, Omar Deeb, Ramón Garduño-Juárez, Guillermo Ramírez-Galicia
    Pages 319-333
Back to top

Keywords

About this book

This volume presents examples of how ANNs are applied in biological sciences and related areas. Chapters focus on the analysis of intracellular sorting information, prediction of the behavior of bacterial communities, biometric authentication, studies of Tuberculosis, gene signatures in breast cancer classification, 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: Second Edition aids scientists in continuing to study Artificial Neural Networks (ANNs).

Editors and Affiliations

  • Chemistry Department, Oxford University, UK, and University of Victoria, Victoria, Canada

    Hugh Cartwright

Bibliographic Information

  • Book Title: Artificial Neural Networks

  • Editors: Hugh Cartwright

  • Series Title: Methods in Molecular Biology

  • DOI: https://doi.org/10.1007/978-1-4939-2239-0

  • Publisher: Springer New York, NY

  • eBook Packages: Springer Protocols

  • Copyright Information: Springer Science+Business Media New York 2015

  • Hardcover ISBN: 978-1-4939-2238-3Published: 11 December 2014

  • Softcover ISBN: 978-1-4939-4893-2Published: 30 April 2017

  • eBook ISBN: 978-1-4939-2239-0Published: 10 December 2014

  • Series ISSN: 1064-3745

  • Series E-ISSN: 1940-6029

  • Edition Number: 2

  • Number of Pages: XI, 340

  • Number of Illustrations: 27 b/w illustrations, 65 illustrations in colour

  • Topics: Cell Biology

Publish with us

Policies and ethics

Back to top

Search

Navigation