Today, biological sequence data is available for biologists to translate analyses from datasets into knowledge that elucidates questions relating to evolution, biological function, and disease. This book introduces the computational and statistical methods required to facilitate these analyses. It progresses from analysis of a single sequence to those with increasing complexity, allowing the authors to discuss methods and techniques in the simplest setting before introducing more complicated material. No advanced knowledge of computer science, statistics, or biology is assumed, making it an ideal textbook for advanced undergraduate and graduate students.
Features optional boxes with information about interesting sidelights and experimental techniques
Takes a problems approach to facilitate enquiry-based learning in the classroom and for self-study
Reviews the most useful database resources
Includes sample data sets for self-study and Web exercises
Lists examples
Each chapter concludes with a list of further readings and helpful resources
Supplementary website features datasets, links to databases, and additional problem sets
Discusses the use of BioPerl to automate data retrieval
Concludes with the authors? perspective on the future of comparative sequence analysis
Authors use an innovative approach to introduce techniques and methods in a progressive fashion starting from the simplest (one sequence) case and ending with analysis of complex, large data sets.
Small datasets presented in each chapter can be used as inquiry datasets to highlight biologically interesting properties or questions.
References are given to sources for more thorough theoretical treatments, and to web sites containing the latest on-line documentation for use of software programs.
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