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Computing for Biologists

Python Programming and Principles

Specificaties
Paperback, 218 blz. | Engels
Cambridge University Press | e druk, 2014
ISBN13: 9781107642188
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Cambridge University Press e druk, 2014 9781107642188
Verwachte levertijd ongeveer 9 werkdagen

Samenvatting

Computing is revolutionizing the practice of biology. This book, which assumes no prior computing experience, provides students with the tools to write their own Python programs and to understand fundamental concepts in computational biology and bioinformatics. Each major part of the book begins with a compelling biological question, followed by the algorithmic ideas and programming tools necessary to explore it: the origins of pathogenicity are examined using gene finding, the evolutionary history of sex determination systems is studied using sequence alignment, and the origin of modern humans is addressed using phylogenetic methods. In addition to providing general programming skills, this book explores the design of efficient algorithms, simulation, NP-hardness, and the maximum likelihood method, among other key concepts and methods. Easy-to-read and designed to equip students with the skills to write programs for solving a range of biological problems, the book is accompanied by numerous programming exercises, available at www.cs.hmc.edu/CFB.

Specificaties

ISBN13:9781107642188
Taal:Engels
Bindwijze:Paperback
Aantal pagina's:218

Inhoudsopgave

Preface; Meet python; Part I. Python versus Pathogens: 1. Computing GC content; 2. Pathogenicity islands; 3. Open reading frames and genes; 4. Finding genes (at last!); Part II. Sequence Alignment and Sex Determination: 5. Recursion; 6. The use-it-or-lose-it principle; 7. Dictionaries, memoization, and speed; 8. Sequence alignments and the evolution of sex chromosomes; Part III. Phylogenetic Reconstruction and the Origin of Modern Humans: 9. Representing and working with trees; 10. Drawing trees; 11. The UPGMA algorithm; Part IV. Additional Topics: 12. RNA secondary structure prediction; 13. Gene regulatory networks and the maximum likelihood method; 14. Birds, bees, and genetic algorithms; Where to go from here; Index.

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        Computing for Biologists