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.
Basic Principles
The Data
Data Quality
Data Representation
Genome Sequence Analysis
Basic Concepts
Genome Sequencing
Finding the Genes
Statistical Methods to Search for Genes
Comparative Genomics
A Virtual Window on Genomes: The World Wide Web
Protein Evolution
Basic Concepts
Molecular Evolution
How to Align Two Similar Sequences
Similarity Matrices
Penalties for Insertions and Deletions
The Alignment Algorithm
Multiple Alignments
Phylogenetic Trees
Similarity Searches in Databases
Basic Principles
The Methods
Amino Acid Sequence Analysis
Basic Principles
Search for Sequence Patterns
Feature Extraction
Secondary Structure: Part One
Prediction of the Three-Dimensional Structure of a Protein
Basic Principles
The CASP Experiment
Secondary Structure Prediction: Part Two
Long-Range Contact Prediction
Predicting Molecular Complexes: Docking Methods
Homology Modeling
Basic Principles
The Steps of Comparative Modeling
Accuracy of Homology Models
Manual versus Automatic Models
Practical Notes
Summing Up
Fold Recognition Methods
Basic Principles
Profile-Based Methods
Threading Methods
The Fold Library
How Well Do These Methods Work?
New Fold Modeling
Basic Principles
Estimating the Energy of a Protein Conformation
Energy Minimization
Molecular Dynamics
The “Omics” Universe
Basic Principles
Transcriptomics
Proteomics
Interactomics
Structural Genomics
Pharmacogenomics
But This Is Not All
Useful Web Sites
Index
A Glossary, References, and Problems appear in each chapter.
Biography
Anna Tramontano
“… 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)