Bioinformatics: Sequence Alignment and Markov Models

by: Kal Renganathan Sharma


Abstract: A state-of-the-art textbook on bioinformatics covering the latest 21st-century technology. An essential tool, this book explores the cutting-edge methods of bioinformatics, presenting a wide range of diagrams, mathematical equations, worked examples, and exercises to illustrate the concepts and models.Bioinformatics discusses auto-immune disorders and enumerates the motivation for sequence alignment. The text provides gene-finding algorithms and introduces binomial heap for the maximum increasing subsequence problem. There is also a wealth of information on suffix trees…HMM…HMM applications…protein secondary structure… microarray techniques…drug discovery and development…and advances in biochip and genome completions and sequence alignment. In addition, this valuable resource includes a listing of Internet sites in bioinformatics, which contain constantly updated information on this fast-changing field.
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Book Details

Title: Bioinformatics: Sequence Alignment and Markov Models

Publisher: : New York, Chicago, San Francisco, Lisbon, London, Madrid, Mexico City, Milan, New Delhi, San Juan, Seoul, Singapore, Sydney, Toronto

Copyright / Pub. Date: 2009 The McGraw-Hill Companies, Inc.

ISBN: 9780071593069

Authors:

Kal Renganathan Sharma Ph.D., P.E., has written five books, 11 journal articles, and hundreds of conference papers. He has held a number of high-level positions at engineering colleges and universities. Dr. Sharma currently teaches at Prairie View A&M University in Prairie View, Texas.

Description: A state-of-the-art textbook on bioinformatics covering the latest 21st-century technology. An essential tool, this book explores the cutting-edge methods of bioinformatics, presenting a wide range of diagrams, mathematical equations, worked examples, and exercises to illustrate the concepts and models.Bioinformatics discusses auto-immune disorders and enumerates the motivation for sequence alignment. The text provides gene-finding algorithms and introduces binomial heap for the maximum increasing subsequence problem. There is also a wealth of information on suffix trees…HMM…HMM applications…protein secondary structure… microarray techniques…drug discovery and development…and advances in biochip and genome completions and sequence alignment. In addition, this valuable resource includes a listing of Internet sites in bioinformatics, which contain constantly updated information on this fast-changing field.