BiBC Essentials

FaculteitFaculty of Science

NiveauMaster

Studiejaar2026-2027

Beschrijving

Course goals

General:

We are going to prepare you for your internship by teaching you essential skills & knowledge
Community building among students.
Getting to know the group leaders and their research.
Become computational: Learn to write scripts in Unix, make pipelines using bioinformatic methods, and learn about version control.
Become familiar with common bioinformatic and biocomplexity methods (algorithms).
Learn to interpret data by modeling
Become a quantitative biologist

Learning goals

general

·         Can read and understand primary literature and critically evaluate their own understanding
·         Can understand and adapt an existing workflow to perform a systematic and reproducible bioinformatics analysis
·         Understands the FAIR principles and the issues related to handling, storage and sharing of data and code

bioinformatics

·         Understand, explain and apply the basics of dimension reduction, clustering (linkage and distances) and visualisation of high dimensional data
·         Can understand and explain the concept of supervised/unsupervised machine learning and their limitations
·         Understand and explain the concepts of cross-validation and overtraining
·         Understands and explain the basics of Hidden Markov Models and its fields of application

biocomplexity

·         Understand and explain the parameter curse and ways to avoid excessive parameter numbers
·         Understand, explain and apply model parameter fitting
·         Understand and explain the relevance of space, stochasticity and multiple scales for model behaviour
·         Understand and explain basic concepts in network theory and motifs
·         Understand and explain basic concepts of excitable media and their applicability to a broad range of biological phenomena
·         Understand the basics of numerical integration

Content

Description of content

In this 6 weeks course the most essential trades for Bioinformatics and BioComplexity will be taught. Short lectures are alternated with hands-on computer practicals and assignments.

Topics that will be covered are: Using the lunix command line and tools.

Building analysis pipelines

Introduction in the many algorithms (and tools) that are used in Bioinformatics and BioComplexity amongst which are: Unix workflows, Version Control, unsupervised learning, parameter fitting, reduction, supervised learning and spatial models

Literature/study material used:

Will be provided as course materials.

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