Biological sequence analysis

Probabilistic and nucleic acids

Richard Durbin, Sean Eddy, Anders Krogh, Graeme Mitchinson

356 pages, parution le 01/04/1998

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Résumé

Probabilistic models are becoming increasingly important in analysing 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 analysing 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 aims to be accessible to molecular biologists, computer scientists, and mathematicians with no formal knowledge of the other fields, and at the same time present the state-of-the-art in this new and highly important field.

There's nothing else - a much-needed textbook in a new and rapidly expanding area of science

Interdisciplinary - aimed at both biologists and computer scientists

Up-to-the-minute - presents the most recent sequence analysis methods and their underlying concepts in a coherent framework

Sommaire

Introduction
Pairwise sequence alignment
Multiple alignments
Hidden Markov models
Hidden Markov models applied to biological sequences
The Chomsky hierarchy of formal grammars
RNA and stochastic context-free grammars
Phylogenetic trees
Phylogeny and alignment
Index

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Caractéristiques techniques

	PAPIER
Éditeur(s)	Cambridge University Press
Auteur(s)	Richard Durbin, Sean Eddy, Anders Krogh, Graeme Mitchinson
Parution	01/04/1998
Nb. de pages	356
Format	16,5 x 24,5
Couverture	Broché
Poids	632g
Intérieur	Noir et Blanc
EAN13	9780521629713
ISBN13	978-0-521-62971-3