Artificial Neural Networks

ISBN-13: 9781493948932 / Angielski / Miękka / 2017 / 340 str.

Hugh Cartwright

Spis treści

1. Introduction To The Analysis Of The Intracellular Sorting Information In Protein Sequences: From Molecular Biology To Artificial Neural Networks

R. Claudio Aguilar

 

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

Yang Shen and Ad Bax

 

3. Predicting Bacterial Community Assemblages using an Artificial Neural Network Approach

Peter Larsen, Yang Dai and Frank R. Collart

 

4. A General ANN-Based Multi-Tasking Model For The Discovery Of Potent and Safer Antibacterial Agents

A. Speck-Planche  and M. N. D. S. Cordeiro

 

5. Use of Artificial Neural Networks in the QSAR Prediction of Physico-chemical Properties and Toxicities for REACH Legislation

John C. Dearden and Philip H. Rowe

 

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

J. H. Miller, B. T. Schrom, and L. J. Kangas

 

7. Prediction of Bioactive Peptides using Artificial Neural Networks

David Andreu and Marc Torrent

 

8. AutoWeka: Towards an Automated Data Mining Software for QSAR and QSPR Studies

Chanin Nantasenamat, Apilak Worachartcheewan, Saksiri Jamsak, Likit Preeyanon, Watshara Shoombuatong, Saw Simeon, Prasit Mandi, Chartchalerm Isarankura-Na-Ayudhya and  Virapong Prachayasittikul

 

9. Ligand Biological Activity Predictions Using Fingerprint-based Artificial Neural Networks (FANN-QSAR)

Kyaw Z. Myint and Xiang-Qun Xie

 

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

Eshel Faraggi and Andrzej Kloczkowski

 

11. Modulation of Grasping Force in Prosthetic Hands Using Neural Network-based Predictive Control

Cristian F. Pasluosta and Alan W.L. Chiu

 

12. Application of Artificial Neural Networks in Computer-aided Diagnosis

Bei Liu

 

13. Developing A Multimodal Biometric Authentication System Using Soft Computing Methods

Mario Malcangi

 

14. Using Neural Networks To Understand The Information That Guides Behaviour: A Case Study In Visual Navigation

Andrew Philippides, Paul Graham, Bart Baddeley and Philip Husbands

 

15. Jump Neural Network For Real-Time Prediction Of Glucose Concentration

Chiara Zecchin, Andrea Facchinetti, Giovanni Sparacino and Claudio Cobelli

 

16. Preparation of Ta-O-based Tunnel Junctions To Obtain Artificial Synapses Based On Memristive Switching

Stefan Niehörster and Andy Thomas

 

17. Architecture and Biological Applications of Artificial Neural Networks: a Tuberculosis Perspective

Jerry A Darsey    

 

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

Sandhya Samarasinghe and Amphun Chaiboonchoe

 

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

Narelle Montañez-Godínez, Aracely C. Martínez-Olguín, Omar Deeb, Ramón Garduño-Juárez, Guillermo Ramírez-Galicia

 

 

Blurb

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).