Pattern Discovery in Bioinformatics (Theory & Algorithms)

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.