Biological Sequence Analysis: Probabilistic Models of Proteins and Nucleic Acids

Cambridge University Press
1
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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.
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Additional Information

Publisher
Cambridge University Press
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Published on
Apr 23, 1998
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Pages
332
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ISBN
9781139457392
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Language
English
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Genres
Science / Biotechnology
Science / Life Sciences / Genetics & Genomics
Science / Life Sciences / Molecular Biology
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Content Protection
This content is DRM protected.
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Jean-Michel Claverie
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