Crisp, clean pages except for a droplet spot on page vi; no other owners' or use marks; square, uncreased spine; soft cover shows only very mild corner wear. Overall excellent. xi, 356pp. incl. index.

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Bibliographic Details

Title

Biological Sequence Analysis: Probabilistic Models of Proteins and Nucleic Acids

Publisher

Cambridge University Press

Publication Date

2001

Language

English

ISBN 10

0521629713

ISBN 13

9780521629713

Binding

Paperback

Condition

Very Good+

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Science & Mathematics

About this title

Synopsis

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.

Book Description

Probabilistic methods are assuming greater significance in the analysis of nucleotide sequence data. This book provides the first unified, up-to-date and self-contained account of such methods, and more generally of probabilistic methods of sequence analysis, presented in a Bayesian framework.

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