Methods for Computational Gene Prediction (Record no. 294614)

MARC details
000 -LEADER
fixed length control field 01891nam a2200157Ia 4500
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9780521706940
082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 572.860285 MAJ-M
100 ## - MAIN ENTRY--PERSONAL NAME
Personal name William H Majoros
245 ## - TITLE STATEMENT
Title Methods for Computational Gene Prediction
260 ## - PUBLICATION, DISTRIBUTION, ETC.
Place of publication, distribution, etc. New York
Name of publisher, distributor, etc. Cambridge University Press
Date of publication, distribution, etc. 2007
300 ## - PHYSICAL DESCRIPTION
Extent xvii, 430 pages : illustrations ; 26 cm
505 ## - FORMATTED CONTENTS NOTE
Formatted contents note 1. Introduction -- 2. Mathematical preliminaries -- 3. Overview of gene prediction -- 4. Gene finder evaluation -- 5. A toy Exon finder -- 6. Hidden Markov models -- 7. Signal and content sensors -- 8. Generalized hidden Markov models -- 9. Comparative gene finding -- 10. Machine Learning methods -- 11. Tips and tricks -- 12. Advanced topics
520 ## - SUMMARY, ETC.
Summary, etc. 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.
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Genomics -- Data processing. Bioinformatics. Molecular genetics -- Data processing.
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type Book
Holdings
Withdrawn status Lost status Damaged status Not for loan Home library Current library Shelving location Date acquired Total Checkouts Full call number Barcode Date last seen Price effective from Koha item type
        Dept. of Computational Biology and Bioinformatics Dept. of Computational Biology and Bioinformatics Processing Center 01/09/2015   572.860285 MAJ-M DCB1249 01/09/2015 19/07/2019 Book