For many of its history, our knowledge of evolution has been based heavily on theoretical models and hypotheses. In the age of novel experimental and technological approaches, we are now increasingly able to evaluate this theory; however, the basics of how and why to develop and analyze a simple model are often forgotten in the process of NGS analysis. This course aims at training evolutionary biologists in classical modeling and teach them ways to approach their own research questions through evolutionary theory.
Primarily through interactive hands-on sessions, complemented by an introduction to the cornerstones of modeling and its application to data analysis, this course will familiarize the participants with ways of approaching a research question with a simple model, and different strategies at gaining insight from the model. In groups of two, course participants will develop and analyze their own toy model in the course and present their findings to the group on the last day.
Topics that will be covered in the course include the following:
Why and how are models useful?
How to write down/develop a model
How simple/complicated should a model be?
Which modeling approach/programming language should I use for my question?
How to nail down a question with a model
Extracting results from an equation/simulation
How to evaluate a model using empirical data
Participants can use their preferred programming language during the hands-on sessions, and free access to Wolfram Mathematica will be provided. The instructors have modeling experience using Mathematica, R, Python, and C++.