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.

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