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Neural Networks and Genome Informatics, Volume 1 (Methods in Computational Biology and Biochemistry) download epub

by C.H. Wu,J.W. McLarty


Epub Book: 1490 kb. | Fb2 Book: 1766 kb.

Performance issues with the use of neural networks in genome informatics should have been given a more careful treatment. Considering its price, this is disappointing.

Series: Methods in Computational Biology and Biochemistry (Book 1). Hardcover: 220 pages. ISBN-13: 978-0080428000. Product Dimensions: . x . inches. Shipping Weight: . pounds. Performance issues with the use of neural networks in genome informatics should have been given a more careful treatment. An instructor in a course in bioinformatics might use this book as a reference source however.

Those who have used neural networks in other fields might be able to use the book as a guide to applying them to genome informatics.

ing neural networks for genome This book appears as Volume I of. Methods in Computational Biology . tional Biology and Biochemistry Series in. the near future. Yunfeng Wu. Beijing University of Posts. and Telecommunications.

ing neural networks for genome. informatics applications and broad re-. views of state-of-the-art methods and their. Konopka), and it is currently the only. IEEE Engineering in medicine and biology magazine january/february 2003.

This book is a comprehensive reference in the field of neural networks and genome informatics. The tutorial of neural network foundations introduces basic neural network technology and terminology.

Chapter 1. Neural Networks for Genome Informatics. Integration of Statistical Methods into Neural Network Applications. This book is a comprehensive reference in the field of neural networks and genome informatics. What Is Genome Informatics?. 1 Gene Recognition and DNA Sequence Analysis. 2 Protein Structure Prediction. 3 Protein Family Classification and Sequence Analysis. 1. Problems in Model Development. 1 Input Variable Selection. 2 Number of Hidden Layers and Units. 3 Comparison of Architectures.

On July 20, we had the largest server crash in the last 2 years This book is a comprehensive reference in the field of neural networks and genome informatics.

On July 20, we had the largest server crash in the last 2 years.

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cle{Wu2003NeuralNA, title {Neural networks and genome informatics (methods in computational biology and biochemistry, volume 1) }, author {Yunfeng Wu}, journal {IEEE Engineering in Medicine and Biology Magazine}, year {2003}, volume {22}, pages {94-94} }. Published in IEEE Engineering in Medicine and Biology Magazine 2003. ticipants related to the programs, to each other, and to the program’s lasting effects on both their personal and professional lives

Methods in Computational Biology and Biochemistry, V.

Methods in Computational Biology and Biochemistry, V. English. AbeBooks may have this title (opens in new window).

Neural Networks and Genome Informatics (Methods in Computational Biology and Biochemistry) by C H Wu and J W McLarty

Neural Networks and Genome Informatics (Methods in Computational Biology and Biochemistry) by C H Wu and J W McLarty. 6. Connecting Medical Informatics and Bio-informatics: Proceedings of MIE2005 (Studies in Health Technology and Informatics) by R Engelbrecht and A Geissbuhler. 7. Bio-Informatics by Sangita. 8. Bio-Informatics by Mustafa Man and Julaily Aida Jusoh. 9. Fundamentals of Bioinformatics by Harisha S. 10. Introduction to mathematical methods in bio informatics by J P Agarwal.

This book is a comprehensive reference in the field of neural networks and genome informatics. The tutorial of neural network foundations introduces basic neural network technology and terminology. This is followed by an in-depth discussion of special system designs for building neural networks for genome informatics, and broad reviews and evaluations of current state-of-the-art methods in the field. This book concludes with a description of open research problems and future research directions.

Comments: (2)

Sharpbringer
This book serves well to introduce the reader to the literature on the applications of neural networks to bioinformatics. It falls short however in giving an in-depth view of how neural networks operate and does not include any source code. Performance issues with the use of neural networks in genome informatics should have been given a more careful treatment. Considering its price, this is disappointing. A reader could obtain the required reading material on this subject from an online search. An instructor in a course in bioinformatics might use this book as a reference source however. Those who have used neural networks in other fields might be able to use the book as a guide to applying them to genome informatics. Thus the book could be viewed as a (very expensive) literature review article, but it does include some interesting remarks at various places: 1. Amino acid groupings that are found automatically by a Kohonen self-organizing map. 2. Feature representation and input encoding. 3. The discussion on cross-validation. 4. The discussion on protein secondary structure prediction. Genetic algorithms are mentioned here, so readers not familiar with these will have to gain the background elsewhere.
Jorius
This is a book that comes out at the right time, a time when tons of information from genomics and several improved analysis tools based on great ideas are both becoming available. I believe readers from a broad range of academic background will benefit from the integration of knowledges from genome informatics, statistics, computer science, engineering, and mathmatics, a feature that this book exemplifies.
Neural Networks and Genome Informatics, Volume 1 (Methods in Computational Biology and Biochemistry) download epub
Computer Science
Author: C.H. Wu,J.W. McLarty
ISBN: 0080428002
Category: Computers & Technology
Subcategory: Computer Science
Language: English
Publisher: Elsevier Science; 1 edition (October 5, 2000)
Pages: 220 pages