Neural Networks And Genome Informatics

E-Book Overview

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.

E-Book Content

Neural Netvirorks and Genome Informatics METHODS IN COMPUTATIONAL BIOLOGY AND BIOCHEMISTRY Volume 1 Series Editor A.K. KONOPKA Maryland, USA ELSEVIER Amsterdam - Lausanne - New York - Oxford - Shannon - Singapore - Tokyo Neural Networks and Genome Informatics C.H. Wu J.W. McLarty University of Texas Health Center at Tyler Department of Epidemiology and Biomatfiematics 11937 U.S. Highway 271 Tyler, TX 75708-3154 USA 2000 ELSEVIER Amsterdam - Lausanne - New York - Oxford - Shannon - Singapore - Tokyo ELSEVIER SCIENCE Ltd The Boulevard, Langford Lane Kidlington, Oxford 0X5 1GB, UK © 2
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