Pattern Discovery in Bioinformatics: Theory & Algorithms

Laxmi Parida

July 4, 2007 by Chapman and Hall/CRC
Reference - 512 Pages - 95 B/W Illustrations
ISBN 9781584885498 - CAT# C5491
Series: Chapman & Hall/CRC Mathematical and Computational Biology

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Features

  • Covers a broad range of topics from the fundamentals of pattern discovery algorithms to basic statistics to state-of-the-art implementation techniques
  • Clarifies how computational methods work and what problems they solve
  • Introduces basic algorithmic concepts, such as trees, before exploring them in detail
  • Focuses on models of biological sequences, including DNA, RNA, and protein sequences
  • Includes illustrative proofs to justify concise factual statements as well as exercises at the end of each chapter for self-study or classroom teaching
  • Summary

    The computational methods of bioinformatics are being used more and more to process the large volume of current biological data. Promoting an understanding of the underlying biology that produces this data, Pattern Discovery in Bioinformatics: Theory and Algorithms provides the tools to study regularities in biological data.

    Taking a systematic approach to pattern discovery, the book supplies sound mathematical definitions and efficient algorithms to explain vital information about biological data. It explores various data patterns, including strings, clusters, permutations, topology, partial orders, and boolean expressions. Each of these classes captures a different form of regularity in the data, providing possible answers to a wide range of questions. The book also reviews basic statistics, including probability, information theory, and the central limit theorem.

    This self-contained book provides a solid foundation in computational methods, enabling the solution of difficult biological questions.