Evolution takes place in large populations over long time and geographic scales. Due to these constraints, mathematical and computational approaches have been used to study evolution since the 1920's, leading to important developments in modern statistics, mathematics, and computer science. In this talk we will see how Scientific Python can be used to study evolutionary theory using mathematical and computational models. We'll see how to run fast evolutionary simulations with NumPy, analyze and visualize simulation results with Pandas and Seaborn, and find solutions to evolutionary models using SciPy and SymPy. Everything will be done in an open GitHub repo and presented using an online Jupyter Notebook to allow listeners to participate. This talk is a wonderful opportunity to discover how theoretical evolutionary biologists approach their research, as well as an occasion to learn about Scientific Python through actual research-based examples.
Slides available here: http://il.pycon.org/2016/static/sessions/yoav-ram.pdf and also: https://github.com/yoavram/PyConIL2016