Chapman and Hall/CRC
192 pages | 8 Color Illus. | 68 B/W Illus.
Guiding readers from the elucidation and analysis of a genomic sequence to the prediction of a protein structure and the identification of the molecular function, Introduction to Bioinformatics describes the rationale and limitations of the bioinformatics methods and tools that can help solve biological problems. Requiring only a limited mathematical and statistical background, the book shows how to efficiently apply these approaches to biological data and evaluate the resulting information.
The author, an expert bioinformatics researcher, first addresses the ways of storing and retrieving the enormous amount of biological data produced every day and the methods of decrypting the information encoded by a genome. She then covers the tools that can detect and exploit the evolutionary and functional relationships among biological elements. Subsequent chapters illustrate how to predict the three-dimensional structure of a protein. The book concludes with a discussion of the future of bioinformatics.
Even though the future will undoubtedly offer new tools for tackling problems, most of the fundamental aspects of bioinformatics will not change. This resource provides the essential information to understand bioinformatics methods, ultimately facilitating in the solution of biological problems.
“… Overall, the book is well organized and clearly written. This book is a good mixture of theory and practical applications. … graduate and research students of biostatistics who want to pursue a career in experimental biology will enjoy this book. In addition, practitioners in cancer research and forensic science will find this book quite useful. I also recommend it for library purchase.”
—Kuldeep Kumar (Bond University), Journal of the Royal Statistical Society
"…Introduction to Bioinformatics serves a noble purpose … Tramontano’s added emphasis on proteomics should serve as an indication of a major current focus of bioinformatics and also to welcome Introduction to Bioinformatics into the canon of bioinformatics-related literature."
—Eric D. Foster, University of Iowa, The American Statistician, August 2008
"This book provides a nice summary of introductory topics in bioinformatics, suitable for higher-level undergraduates with some biological background looking to enter the field or masters-level graduate students. … the subject matter is informative and well written for an introductory book."
—International Statistical Review, 2008
“By reading the book from cover to cover, the reader will acquire a sense of the richness of the field of bioinformatics.”
—Jonathan Hodgson, Zentralblatt Math, Vol. 1115 (2007/17)
The Data: Storage and Retrieval
Genome Sequence Analysis
Finding the Genes
Statistical Methods to Search for Genes
A Virtual Window on Genomes: The World Wide Web
How to Align Two Similar Sequences
Penalties for Insertions and Deletions
The Alignment Algorithm
Similarity Searches in Databases
Amino Acid Sequence Analysis
Search for Sequence Patterns
Secondary Structure: Part One
Prediction of the Three-Dimensional Structure of a Protein
The CASP Experiment
Secondary Structure Prediction: Part Two
Long-Range Contact Prediction
Predicting Molecular Complexes: Docking Methods
The Steps of Comparative Modeling
Accuracy of Homology Models
Manual versus Automatic Models
Fold Recognition Methods
The Fold Library
How Well Do These Methods Work?
New Fold Modeling
Estimating the Energy of a Protein Conformation
The “Omics” Universe
But This Is Not All
Useful Web Sites
A Glossary, References, and Problems appear in each chapter.
This series aims to capture new developments in computational biology, as well as high-quality work summarizing or contributing to more established topics. Publishing a broad range of reference works, textbooks, and handbooks, the series is designed to appeal to students, researchers, and professionals in all areas of computational biology, including genomics, proteomics, and cancer computational biology, as well as interdisciplinary researchers involved in associated fields, such as bioinformatics and systems biology.