Bioinformatics: Sequence and Genome Analysis (2nd Edition)

As more species' genomes are sequenced, computational analysis of these data has become increasingly important. The second, entirely updated edition of this widely praised textbook provides a comprehensive and critical examination of the computational methods needed for analyzing DNA, RNA, and protein data, as well as genomes. The book has been rewritten to make it more accessible to a wider audience, including advanced undergraduate and graduate students. New features include chapter guides and explanatory information panels and glossary terms. New chapters in this second edition cover statistical analysis of sequence alignments, computer programming for bioinformatics, and data management and mining. Practically oriented problems at the ends of chapters enhance the value of the book as a teaching resource. The book also serves as an essential reference for professionals in molecular biology, pharmaceutical, and genome laboratories. This Book Is An Ideal Foundation For Teaching At The Undergraduate And Graduate Levels. It Is Also Highly Suited For Self-instruction By Research Investigators Interested In Applying Computational Methods Of Analysis And By Information Technologists Associated With Academic And Industrial Laboratories.--jacket. Historical Introduction And Overview -- Collecting And Storing Sequences In The Laboratory -- Alignment Of Pairs Of Sequences -- Introduction To Probability And Statistical Analysis Of Sequence Alignments -- Multiple Sequence Alignment -- Sequence Database Searching For Similar Sequences -- Phylogenetic Prediction -- Prediction Of Rna Secondary Structure -- Gene Prediction And Regulation -- Protein Classification And Structure Prediction -- Genome Analysis -- Bioinformatics Programming Using Perl And Perl Modules -- Analysis Of Microarrays. David W. Mount. Includes Bibliographical References And Index. This chapter describes how bioinformatics has evolved into a new field of scientific investigation, describes the roles of biological and computational research in this field, and provides a brief historical account.