720 pages, 11 colour & 91 b/w illustrations, 3 tables
Do you have a biological question that could be readily answered by computational techniques, but little experience in programming? Do you want to learn more about the core techniques used in computational biology and bioinformatics? Written in an accessible style, Python Programming for Biology provides a foundation for both newcomers to computer programming and those interested in learning more about computational biology. The chapters guide the reader through: a complete beginners' course to programming in Python, with an introduction to computing jargon; descriptions of core bioinformatics methods with working Python examples; scientific computing techniques, including image analysis, statistics and machine learning. Python Programming for Biology also functions as a language reference written in straightforward English, covering the most common Python language elements and a glossary of computing and biological terms. Python Programming for Biology will teach undergraduates, postgraduates and professionals working in the life sciences how to program with Python, a powerful, flexible and easy-to-use language.
2. Beginners' guide
3. Python basics
4. Program control and logic
7. Object orientation
8. Object data modelling
10. Coding tips
11. Biological sequences
12. Pairwise sequence alignments
13. Multiple sequence alignments
14. Sequence variation and evolution
15. Macromolecular structures
16. Array data
17. High-throughput sequence analyses
19. Signal processing
23. Clustering and discrimination
24. Machine learning
25. Hard problems
26. Graphical interfaces
27. Improving speed
Appendix 1: simplified language reference
Appendix 2: selected standard type methods and operations
Appendix 3: standard module highlights
Appendix 4: string formatting
Appendix 5: regular expressions
Appendix 6: further statistics
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Tim Stevens is Senior Investigator Scientist at the MRC Laboratory of Molecular Biology in Cambridge. He researches single-cell 3D genome architecture and provides computational biology oversight, development and training within the Cell Biology Division.
Wayne Boucher, a mathematician and theoretical physicist by training, is a senior postdoctoral associate and computing technician for the Department of Biochemistry at the University of Cambridge. He teaches undergraduate mathematics and postgraduate programming courses, and is currently developing software for the analysis of biological molecules by nuclear magnetic resonance spectroscopy.