This book will be used to learn Python in workshop settings.
For Biologists, Life Scientists
There are many books, even free books, with the objective to teach Python or other programming languages. I previously wrote a list of free books on the post Free Data Science Books.
This book “Python for the Life Sciences – A Gentle Introduction to Python for Life Scientists” by Alexander Lancaster and Gordon Webster is specifically aimed at life scientists. From the earliest chapters, the author’s goal is to teach the fundamentals of Python using examples common to life scientists.
This is what makes this book more interesting and easier for life scientists.
Are you ready to find out how to use Python to automate lab calculations,search forgene promoter sequences, rotate a molecular bond, drive a 96-well plate robot, build a cellular toggle switch, model animal coat pattern formation, grow a virtual plant, simulate a flu epidemic, or evolve populations? If so, you’ve come to the right place. Ready to go down the rabbit hole? Let’s begin.
See Chapter titles below or online Table of Contents [Archived] for details.
Download for UW
It is available for download to University of Wisconsin personnel when going to doi.org/10.1007/978-1-4842-4523-1 that redirects to the SpringerNature link.
The download formats are PDF or ePub. For physical copy, as of this writing (November 15, 2022) the book is on sale on that site for $9.99 instead of $44.99 as soft cover.
If necessary click “Log in” at top right, which provides a login option with an Institution by clicking on “>> Access via your institution”.
Enter “University of Wisconsin” which will find 3 entries: Madison, Milwaukee , and Stout.
Clicking on “University of Wisconsin-Madison” will then allow you to loging with your NetID
1. Getting started with Python: Setting yourself up to use Python
2. Python at the lab bench: The fundamentals of the Python language
3. Making sense of sequences: Biological sequences and Python data structures
4. A statistical interlude: Of Bayes’ theorem and biomarkers
5. Open doors to your data: Reading, parsing and handling biological data files
6. Finding needles in haystacks: Regular expressions for genomic and sequences
7. Object lessons: Biological sequences as Python objects
8. Slicing and dicing genomic data: Next generation sequencing pipelines
9. The wells! The wells!: Microtiter plate assays I: data structures
10. Well on the way: Microtiter plate assays II: automation and visualization
11. Molecules in 3D: Mathematics and linear algebra for structural biology
(Three-dimensional mathematics and linear algebra for molecular mechanics.)
12. Turning genes on and off: Visualizing biochemical kinetics using matplotlib
13. Taming the network hairball: Using Python sets to mine systems biology data
14. Genetic feedback loops: Modeling gene networks with the Gillespie algorithm
15. Growing a virtual garden: Modeling plant development with L-systems
16. How the leopard got its spots: Cellular automata models of Turing patterns
(Turing’s model of morphogenesis with Python 2D graphics.)
17. Foxes guarding henhouses: Ecological modeling with predator-prey dynamics
18. A virtual flu epidemic: Exploring epidemiology with agent-based models
(virtual flu epidemic. Illustrates Python’s object-oriented programming)
19. Retracing life’s footsteps: Evolutionary dynamics with the Wright-Fisher model
(Wright-Fisher model to demonstrate natural selection in action.)
Epilogue: Because breaking up is hard to do
FAQs on Python
There are many trivia facts that can be gleaned from the Python.org site FAQ page, answer to such questions as:
- First article written about Python (1991)
- Who “invented” Python (Guido van Rossum)
- Why is it called Python? (hint: “Monty Python’s Flying Circus”)
- (and…origin of name “Monty Python’s Flying Circus”)
- Is Python a good language for beginning programmers? (Yes)
- Why was Python created in the first place? (brief summary by by Guido van Rossum)