Biological Sequence Analysis: Probabilistic Models of Proteins and Nucleic Acids / Edition 1

Biological Sequence Analysis: Probabilistic Models of Proteins and Nucleic Acids / Edition 1

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by Richard Durbin, Sean R. Eddy, Anders Krogh, Graeme Mitchison
     
 

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ISBN-10: 0521629713

ISBN-13: 9780521629713

Pub. Date: 05/28/1998

Publisher: Cambridge University Press

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

Overview

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.

Product Details

ISBN-13:
9780521629713
Publisher:
Cambridge University Press
Publication date:
05/28/1998
Edition description:
New Edition
Pages:
368
Product dimensions:
6.85(w) x 9.72(h) x 0.91(d)

Table of Contents

1. Introduction; 2. Pairwise sequence alignment; 3. Multiple alignments; 4. Hidden Markov models; 5. Hidden Markov models applied to biological sequences; 6. The Chomsky hierarchy of formal grammars; 7. RNA and stochastic context-free grammars; 8. Phylogenetic trees; 9. Phylogeny and alignment; Index.

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Biological Sequence Analysis: Probabilistic Models of Proteins and Nucleic Acids 5 out of 5 based on 0 ratings. 1 reviews.
Guest More than 1 year ago
If you want to be in the field of bioinformatics or computational biology you simply MUST read and understand this book. It is a bit dated in some areas (published in 1997) but the topics are sound and well covered. I have read most of the books in this field and this is the best overall book of its kind.