This information sheet indicates how the course will be organized at pandemic code level yellow and green.
If the colour codes change during the academic year to orange or red, modifications are possible, for example to the teaching and evaluation methods.

Introduction to Computational Biology

Course Code :1000WETCOB
Study domain:Computer Science
Academic year:2020-2021
Semester:2nd semester
Contact hours:0
Study load (hours):84
Contract restrictions: No contract restriction
Language of instruction:Dutch
Exam period:exam in the 2nd semester
Lecturer(s)Kris Laukens

3. Course contents *

Computational biology consists of the use of techniques such as computational simulations, data analysis and mathematical modeling to study a large collection of biological problems.

In this course we will always start from a specific biological problem and discuss how computational techniques are used to obtain a solution.

For some of the topics we will involve external experts. Each of these topics starts with the definition of the biological problem, in a way that does not assume prior biological knowledge. Some examples of topics (possibly) covered:

  • Study of metabolic fluxes.
  • Modelling of growth
  • Modelling of locomotion
  • Climate models
  • Biological evolution
  • Computational neurobiology
  • Social networks and population dynamics
  • Molecular interaction networks
  • Bio-inspired computing
  • Ciomputing with biomolecules
  • Genetics

There exist quite a few different definitions of computational biology, making the distinction with bioinformatics not always clear. In UAntwerpen curriculum we offer both courses, and we distinguish the fields as follows. Computational biology differs from bioinformatics in terms of both the biological and computational terms of scope. Bioinformatics is a more narrowly defined discipline which focuses on the use of data science and information theory techniques for interpreting biomolecular data such as DNA and RNA. Computational biology involves a much wider range of biological applications, and also makes use of mathematical modeling and computer simulations.