Sequence - Evolution - Function (eBook)

Sequence - Evolution - Function is an introduction to the computational approaches that play a critical role in the emerging new branch of biology known as functional genomics. The book provides the reader with an understanding of the principles and approaches of functional genomics and of the potential and limitations of computational and experimental approaches to genome analysis. Key topics covered in this textbook are: *the completed and ongoing genome sequencing projects, *databases that store and organize genomic data, with their unique advantages and pitfalls, *principles and methods of genome analysis and annotation, *ways to automate the searches and increase search sensitivity while minimizing the error rate, *the first lessons from the Human Genome Project, *the contribution of comparative genomics to the understanding of hereditary diseases and cancer, *fundamental and practical applications of comparative genomics, *the use of complete genomes for evolutionary analysis, *the application of comparative genomics for identification of potential drug targets in microbial genomes, *Problems for Further Study, which are designed to be solved by using methods available through the WWW. Sequence - Evolution - Function should help bridge the "e;digital divide"e; between biologists and computer scientists, allowing biologists to better grasp the peculiarities of the emerging field of Genome Biology and to learn how to benefit from the enormous amount of sequence data available in the public databases. The book is non-technical with respect to the computer methods for genome analysis and discusses these methods from the user's viewpoint, without addressing mathematical and algorithmic details. Prior practical familiarity with the basic methods for sequence analysis is a major advantage, but a reader without such experience will be able to use the book as an introduction to these methods. This book is perfect for introductory level courses in computational methods for comparative and functional genomics.