Pattern Discovery in Bioinformatics - Theory & Algorithms

Informationen zum Autor Parida! Laxmi Klappentext Taking a systematic approach to pattern discovery! this self-contained book supplies sound mathematical definitions and efficient algorithms to explain vital information about biological data. A solid foundation in computational methods! it explores various data patterns! including strings! clusters! permutations! topology! partial orders! and boolean expressions! to capture a different form of regularity in the data. The book focuses on models of biological sequences! including DNA! RNA! and protein sequences. With numerous exercises at the end of each chapter! it also reviews basic statistics! including probability! information theory! and the central limit theorem. Zusammenfassung Offers the tools to study the regularities in biological data. This book explores various data patterns, including strings, clusters, permutations, topology, partial orders, and boolean expressions. It also reviews basic statistics, including probability, information theory, and the central limit theorem. Inhaltsverzeichnis 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.

Product details

• Authors: Parida Laxmi, Laxmi Parida, Laxmi (Ibm Tj Watson Research Center Parida, Parida Laxmi
• Publisher: Taylor & Francis Ltd.
• Languages: English
• Product format: Hardback
• Released: 04.07.2007
• EAN: 9781584885498
• ISBN: 978-1-58488-549-8
• No. of pages: 526
• Series: Chapman & Hall/CRC Mathematical and Computational Biology; Chapman & Hall/CRC Mathematical and Computational Biology
• Subjects: Natural sciences, medicine, IT, technology > Biology; SCIENCE / Life Sciences / Biology, COMPUTERS / Optical Data Processing, Biology, life sciences, pattern recognition