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Artificial Neural Networks

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Cover of 'Artificial Neural Networks'

Table of Contents

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    Book Overview
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    Chapter 1 Introduction to the analysis of the intracellular sorting information in protein sequences: from molecular biology to artificial neural networks.
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    Chapter 2 Protein Structural Information Derived from NMR Chemical Shift with the Neural Network Program TALOS-N
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    Chapter 3 Predicting bacterial community assemblages using an artificial neural network approach.
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    Chapter 4 A General ANN-Based Multitasking Model for the Discovery of Potent and Safer Antibacterial Agents
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    Chapter 5 Use of Artificial Neural Networks in the QSAR Prediction of Physicochemical Properties and Toxicities for REACH Legislation
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    Chapter 6 Artificial Neural Network for Charge Prediction in Metabolite Identification by Mass Spectrometry
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    Chapter 7 Prediction of Bioactive Peptides Using Artificial Neural Networks
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    Chapter 8 AutoWeka: Toward an Automated Data Mining Software for QSAR and QSPR Studies
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    Chapter 9 Ligand Biological Activity Predictions Using Fingerprint-Based Artificial Neural Networks (FANN-QSAR)
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    Chapter 10 GENN: A GEneral Neural Network for Learning Tabulated Data with Examples from Protein Structure Prediction
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    Chapter 11 Modulation of Grasping Force in Prosthetic Hands Using Neural Network-Based Predictive Control
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    Chapter 12 Application of Artificial Neural Networks in Computer-Aided Diagnosis
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    Chapter 13 Developing a Multimodal Biometric Authentication System Using Soft Computing Methods
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    Chapter 14 Using Neural Networks to Understand the Information That Guides Behavior: A Case Study in Visual Navigation
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    Chapter 15 Jump neural network for real-time prediction of glucose concentration.
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    Chapter 16 Preparation of Ta-O-Based Tunnel Junctions to Obtain Artificial Synapses Based on Memristive Switching
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    Chapter 17 Architecture and Biological Applications of Artificial Neural Networks: A Tuberculosis Perspective
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    Chapter 18 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
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    Chapter 19 QSAR/QSPR as an Application of Artificial Neural Networks
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Mentioned by

6 tweeters
1 Facebook page


9 Dimensions

Readers on

48 Mendeley
1 CiteULike
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Artificial Neural Networks
Published by
Springer New York, December 2014
DOI 10.1007/978-1-4939-2239-0
978-1-4939-2238-3, 978-1-4939-2239-0

Cartwright, Hugh

Twitter Demographics

The data shown below were collected from the profiles of 6 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 48 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 48 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 14 29%
Researcher 6 13%
Student > Bachelor 5 10%
Student > Doctoral Student 4 8%
Student > Master 3 6%
Other 7 15%
Unknown 9 19%
Readers by discipline Count As %
Computer Science 7 15%
Chemistry 7 15%
Biochemistry, Genetics and Molecular Biology 7 15%
Engineering 6 13%
Agricultural and Biological Sciences 5 10%
Other 8 17%
Unknown 8 17%