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.
By:
Laxmi Parida Imprint: Chapman & Hall/CRC Country of Publication: United Kingdom Dimensions:
Height: 234mm,
Width: 156mm,
Weight: 898g ISBN:9780367388898 ISBN 10: 0367388898 Pages: 526 Publication Date:09 April 2020 Audience:
Professional and scholarly
,
Undergraduate
Format:Paperback Publisher's Status: Active
Introduction. Basic Algorithms. Basic Statistics. What Are Patterns? Modeling the Stream of Life. String Pattern Specifications. Algorithms and Pattern Statistics. Motif Learning. The Subtle Motif. Permutation Patterns. Permutation Pattern Probabilities. Topological Motifs. Set-Theoretic Algorithmic Tools. Expression and Partial Order Motifs. References. Index.