Python Programming for Biology

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.

• Preface; Acknowledgements; 1. Prologue; 2. Beginners' guide; 3. Python basics; 4. Program control and logic; 5. Functions; 6. Files; 7. Object orientation; 8. Object data modelling; 9. Mathematics; 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; 18. Images; 19. Signal processing; 20. Databases; 21. Probability; 22. Statistics; 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; Glossary; Index.

'As a long-time advocate of Python as the language of choice for both the bulk of biological data analysis and for teaching computer programming to molecular life scientists, I am delighted to see this book. [It] provides a well-focused introduction to Python programming but then goes on to use the clarity of the Python language to demystify a wide range of commonly applied data processing and analysis techniques that arise in modern cell and molecular biology. The integration of straightforward introductions to sequence analysis, image processing and statistical analysis (amongst others) into a book on Python is inspired. The clarity of the Python language helps to show that often 'yes it really is that simple', in a way that staring at a mathematical expression often fails to, and the programming element allows the reader to become actively involved.' Jeremy Craven, University of Sheffield