Bioinformatics: Volume I: Data, Sequence Analysis and Evolution (Methods in Molecular Biology)

In this book, leading researchers in the field of Bioinformatics provide a selection of the most useful and widely applicable methods, able to be applied as is, or with minor variations, to many specific problems. Over 80 authors from around the globe contribute to the two volumes, including many leading experts in their respective subjects. They encompass topics from across the diverse field of bioinformatics through its broad scope, combining to provide an inter-disciplinary collaboration involving biologists, biochemists, physicists, mathematicians, statisticians and computer scientists.

Not only is the quantity of life science data expanding, but new types of biological data continue to be introduced as a result of technological development and a growing understanding of biological systems. Methods for analyzing these data are an increasingly important component of modern biological research. In Bioinformatics, leading researchers in the field provide a selection of the most useful and widely applicable methods, able to be applied as is, or with minor variations, to many specific problems.  Volume I: Data, Sequence Analysis and Evolution examines a selection of methods involving the generation and organization of data, including sequence data, RNA and protein structures, microarray expression data and functional annotations, methods for discovering the functional components of genomes, whether they be genes, alternative splice sites, non-coding RNAs or regulatory motifs, and several of the most interesting methods in phylogenetics and evolution.  As a volume of the highly successful Methods in Molecular Biology™ series, this work provides the kind of detailed description and implementation advice that is crucial for getting optimal results.

Comprehensive and cutting-edge, Bioinformatics: Volume I: Data, Sequence Analysis and Evolution is an ideal reference for all scientists involved with the ever-growing array of data in the expanding field of life science.