| View Larger Image | Biological Sequence Analysis: Probabilistic Models of Proteins and Nucleic Acids | Paperbackby Richard Durbin (Author), Sean R. Eddy (Author), Anders Krogh (Author), Graeme Mitchison (Author)
| List Price: | $61.00 | | Price: | $48.34 | | You Save: | $12.66 (21%) | | | Available: | Usually ships in 24 hours |
| | Binding: | Paperback | | Publisher: | Cambridge University Press | | Page Count: | 356 Pages | | Publication Date: | July 01, 1999 | | Sales Rank: | 383,459rd |
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EDITORIAL REVIEWS |
Product Description
Probablistic models are becoming increasingly important in analyzing the huge amount of data being produced by large-scale DNA-sequencing efforts such as the Human Genome Project. For example, hidden Markov models are used for analyzing biological sequences, linguistic-grammar-based probabilistic models for identifying RNA secondary structure, and probabilistic evolutionary models for inferring phylogenies of sequences from different organisms. This book gives a unified, up-to-date and self-contained account, with a Bayesian slant, of such methods, and more generally to probabilistic methods of sequence analysis. Written by an interdisciplinary team of authors, it is accessible to molecular biologists, computer scientists, and mathematicians with no formal knowledge of the other fields, and at the same time presents the state of the art in this new and important field. |
CUSTOMER REVIEWS (Average Customer Rating: 4.5 based on 19 reviews)
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nice book by Jianbin Wang  5 Stars
April 16, 2009
very useful book for sequence analysis. i use it as part of my bioinformatics reference in stanford. professor's recommendation!
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Must Have for any Bioinformatics Student by Wyatt Clark (Indiana, USA) 5 Stars
March 03, 2009
This book is a must have for any bioinformatics student working with sequence or genomic data. Useful for anyone attempting to gain an understanding of stochastic models, hidden markov models, and semi-hidden markov models
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Technically brilliant but totally inaccessible by Andrew Dalby (oxford)  2 Stars
April 21, 2008
While this is perhaps the best book on Hidden Markov Models in Bioinformatics available, you would do well to read Rabiner's review paper. For me this is the type of book that would put potential students off bioinformatics for life. It is too technical and uses inappropriate notation. It has too many "It is easily shown" phrases which means that actually the real proof would be rather involved. Dynamic programming is not explained very well.
If you have a maths or computer background then go for it but if you prefer your Bio in Bioinformatics then stay well clear and go for Mount.
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An Excellent Introduction by kprema (Miami, FL, USA) 5 Stars
January 01, 2008
This book gives an excellent introduction into sequence analysis for a person who is already somewhat familiar with the basics of Bayesian techniques. The authors illustrate concepts, as and when they are introduced, via carefully selected examples; comprehension is made much easier because of this.
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Great reference by Mark Schreiber  4 Stars
September 05, 2007
A great reference and a good introduction to many important concepts in sequence analysis. However, if you don't have a reasonable grounding in math you may struggle with the terse notation.
Borodovsky's companion book is an excellent partner for this book. Get both.
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