Master of Science in Bioinformatics
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  • Modelling and Simulation of Biosystems
  • Linux

    • Prerequisites

    When you start this master's program, you have to have obtained a basic knowledge of mathematics, statistics, and programming. To address any potential gaps in some of these concepts, you can take a look at the resources listed per course below.

    Applied High-Throughput Analysis & Statistical Genomics

    The prerequisites are the successful completion of a basic course of statistics that covers topics on data exploration and descriptive statistics, statistical modeling, and inference: linear models, confidence intervals, t-tests, F-tests, anova, chi-squared test. The basis concepts may be revisited in the online course at https://statomics.github.io/PSLS/ (English) and https://statomics.github.io/sbc21/ (Dutch). The Dutch course also has video clips on each concept. Both courses also include all R code for every plot and statistical analysis in the course notes.

    In addition, knowledge of programming in R is preferred. A primer to R and Data visualization in R can be found at:

    These courses include clips in english as well as exercises for which you get automatic feedback.

    For the course of Statistical Genomics, you can find all information on the website https://statomics.github.io/SGA/.

    Machine Learning for Life Sciences

    In the PDF file Prerequisites course Machine Learning for Life Sciences, you can find for each lecture which basic knowledge is required and corresponding Wikipedia links. In addition, basic programming skills, in particular Python (e.g. https://dodona.ugent.be/), are required.

    Selected Topics in Mathematical Optimization

    Following is required:

    • Good knowledge of basic linear algebra and calculus (matrices, differential calculus, integral calculus, ...)
    • Knowledge of basic probability theory (distribution functions, moments, Bayes’ rule, ...)
    • A basic knowledge of (scientific) programming in one of the following languages: C, Python, Julia. (Knowledge of Python: Numpy/Scipy is an advantage). People that have no programming experience are advised to look into introductory courses of Python (e.g. https://dodona.ugent.be/).

    Prior knowledge of numerical algorithms is advantageous but not necessary.

    Modelling and Simulation of Biosystems

    Course website: https://kermit-ugent.github.io/ModSim/

    Linux

    Having some idea about basic concepts in Linux can be helpful.

    Here is the link to the course of Prof. Fostier: https://github.ugent.be/jfostier/DP.

    Another option is this course: "https://swcarpentry.github.io/shell-novice/.

    An excellent introduction is the first lesson of this course: https://missing.csail.mit.edu/.