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Learning Goals - EvoSysBio

Learning goals of this course that are specific to evolutionary systems biology.

Overarching learning objective

The most important goal for this course is for you to improve your ability to: 

Ask good questions and connect the dots.

To learn this well takes a lot of experience in investigating complex systems and a set of research skills that will help you do this. During this course you will get the opportunity to improve these skills and to practice them in the area of evolutionary systems biology, a fascinating new multi-disciplinary field that brings together insights from many other fields:

  • Biological fields like evolution, ecology, genetics, molecular biology, biochemistry, etc. and
  • Quantitative fields like computational modeling, mathematics,  statistics, complex systems analysis, etc.

The goal of combining insights from different fields is to answer more rigorously biological questions that we often only have an intuition for. To make progress in evolutionary systems biology regularly requires collaboration between scientists from different disciplines. Thus, one of the important transferrable skills you will learn in this course is how to interact with researchers from other fields: a key skill in today's complex world.

Learning goals specific to EvoSysBio

Conceptually at a high level, you will learn the following: 

  • Explain the basics of how evolution works mechanistically through population genetic processes.
  • Explain the basics of how molecular systems can be analyzed by simulation in the computer. 
  • Explain the big picture of EvoSysBio and what molecular systems biology and population genetics can contribute using specific examples.
  • Explain fitness landscapes and how specific techniques can be used to overcome the challenges of visualization in specific examples.
  • Explain where systems biology fits into the the various levels of analysis of fitness landscapes that could help compute differences in fitness.
  • Know how to design and interpret a candidate fitness correlate.
  • Explain to someone from another discipline, how your discipline can contribute to bigger questions in EvoSysBio.
Practically, you will learn:
  • How to make it simple to computationally analyze aspects of complex models with the help of Evolvix, a brand new user-friendly model description language that is being developed by the course instructor to make modeling easy.
  • How to build ordinary differential equation models and stochastic simulation models using the Evolvix language.
  • How to document computational models really well, including the motivations and questions behind them.
  • How to discuss interesting questions in EvoSysBio at a high level in a ReLog (like a blog, but focussed on research).
  • How to find a part where you can contribute specific research results linked to a bigger questions.
  • How to write a collaborative research proposal. An important career skill!
  • How to appreciate the contributions from other disciplines and how to ask other researchers for help, where you need it. 

In order to make progress towards these goals, you need to develop your general science skills described on some of the other pages in this folder. While these general learning goals are too big to learn in any single instructional unit, this course will contribute to your development of skills in these areas and the overview might help you to put into context much of what you have already learned (and will continue to learn elsewhere).