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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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