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Teaches life science students how to use Python programming and computational problem-solving in the context of compelling biological applications.
List of contents
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.
About the author
Ran Libeskind-Hadas is the R. Michael Shanahan Professor of Computer Science at Harvey Mudd College, USA, working in the areas of algorithms and computational biology. He is a recipient of both the Iris and Howard Critchell Professorship and the Joseph B. Platt Professorship for teaching, as well as the Distinguished Alumni Educator Award from the University of Illinois, Urbana-Champaign Department of Computer Science.Eliot Bush is Associate Professor of Biology at Harvey Mudd College, USA. His main research interest is the study of evolution. Among other things he has modeled the evolution of metabolism, characterized DNA methylation patterns in insects, developed algorithms for studying substitution bias in DNA, and analyzed a 30-million-year-old primate fossil. His teaching interests focus on incorporating computers and programming assignments into biology coursework.
