Methods for Computational Gene Prediction by William H. Majoros
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Methods for Computational Gene Prediction
By William H. Majoros

Methods for Computational Gene Prediction

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Format: Paperback

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Methods for Computational Gene Prediction by William H. Majoros

Book Description

Inferring the precise locations and splicing patterns of genes in DNA is a difficult but important task, with broad applications to biomedicine. The mathematical and statistical techniques that have been applied to this problem are surveyed and organized into a logical framework based on the theory of parsing. Both established approaches and methods at the forefront of current research are discussed. Numerous case studies of existing software systems are provided, in addition to detailed examples that work through the actual implementation of effective gene-predictors using hidden Markov models and other machine-learning techniques. Background material on probability theory, discrete mathematics, computer science, and molecular biology is provided, making the book accessible to students and researchers from across the life and computational sciences. This book is ideal for use in a first course in bioinformatics at graduate or advanced undergraduate level, and for anyone wanting to keep pace with this rapidly-advancing field.

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Book Details

ISBN: 9780521706940
ISBN-10: 0521706947
Format: Paperback
(247mm x 175mm x 20mm)
Pages: 448
Imprint: Cambridge University Press
Publisher: Cambridge University Press
Publish Date: 16-Aug-2007
Country of Publication: United Kingdom

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Books By Author William H. Majoros

Methods for Computational Gene Prediction by William H. Majoros Methods for Computational Gene Prediction, Hardback (August 2007)

A self-contained, rigorous text describing models used to identify genes in genomic DNA sequences.

» View all books by William H. Majoros

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Author Biography - William H. Majoros

W. H. Majoros is Staff Scientist at the Center for Bioinformatics and Computational Biology, in the Institute for Genome Sciences and Policy at Duke University. He has worked as a research scientist in the fields of computational biology, natural language processing, and information retrieval for over a decade. He was part of the human genome project at Celera Genomics and has taken part in the sequencing and analysis of numerous organisms including human, mouse, fly and mosquito.

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