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Methods for Computational Gene Prediction
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Binding: Paperback
Dewey Decimal Number: 572.860285
EAN: 9780521706940
Edition: 1
ISBN: 0521706947
Label: Cambridge University Press
Manufacturer: Cambridge University Press
Number Of Items: 1
Number Of Pages: 448
Publication Date: September 03, 2007
Publisher: Cambridge University Press
Studio: Cambridge University Press
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Editorial Review:
Inferring the precise locations and splicing patterns of genes in DNA is a difficult but important task, with broad applications to biomedicine. The mathematical and statistical techniques that have been applied to this problem are surveyed and organized into a logical framework based on the theory of parsing. Both established approaches and methods at the forefront of current research are discussed. Numerous case studies of existing software systems are provided, in addition to detailed examples that work through the actual implementation of effective gene-predictors using hidden Markov models and other machine-learning techniques. Background material on probability theory, discrete mathematics, computer science, and molecular biology is provided, making the book accessible to students and researchers from across the life and computational sciences. This book is ideal for use in a first course in bioinformatics at graduate or advanced undergraduate level, and for anyone wanting to keep pace with this rapidly-advancing field.
This advanced text describes in detail the algorithms and models used to identify genes in genomic DNA sequences. It provides the underlying theory of both established techniques and also methods at the forefront of current research and is ideal for use in a first course in bioinformatics or computational biology.
Customer Reviews
Average Rating: 
Rating: - A great reference both for gene prediction and for many basic bioinformatics techniques
I recently sat down to tackle a problem in bioinformatics that was just begging for a hidden markov model with Baum Welch to estimate the emissions and transition probabilities. I had two books at my fingertips: this one and Durbin. I have to say, I found this the more helpful of the two. The explanations are on par with each other but this book takes a slightly more computationally focused approach and provides very clear pseudo-code for all of its more complicated algorithms (Baum Welch, forward, ... Read More
Rating: - An Extraordinary Addition to the Bioinformatics Bookshelf
If you are interested in bioinformatics and the art of gene prediction or genome annotation, you MUST buy this book!! Methods for Computational Gene Prediction was written with both molecular biologists and computer scientists in mind. Although those with training in math and statistics will find some of the material easier to grasp, the book starts out with both a math primer and background on molecular biology to bring both target audiences up to speed. The author, Bill Majoros, did a fantastic ... Read More
Rating: - Additional Info from the Author
Online information for this title (including extensive supplementary material) is available at the book's official web site: http://geneprediction.org/book
Table of Contents
1. Introduction
2. Mathematical Preliminaries
3. Overview of Gene Prediction
4. Gene Finder Evaluation
5. A Toy Exon Finder
6. Hidden Markov Models
7. Signal and Content Sensors
8. Generalized Hidden Markov Models
9. Comparative Gene Finding
10. Machine ... Read More
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