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INFO-G4411

Bioinformatics, Biostatistics

année académique
2025-2026
2026-2027

Titulaire(s) du cours

Vincent DETOURS (Coordonnateur) et Caroline VERHOEVEN

Crédits ECTS

5

Langue(s) d'enseignement

anglais

Contenu du cours

This course is organized in two parts: biostatistics (1/3 of the teaching) and bioinformatics (2/3).

The bioinformatics part of the course focuses on the computational analysis of functional genomic data, i.e. data about products of the genome considered on a genome-wise scale. It starts by presenting microarray technologies and the preprocessing steps required before any biological investigation can be carried out. Next, methods basically extending the pre-genomics, low-throughput gene expression experiments to genome-wide screens are presented. Then the course unfolds with the presentation of recent tools that operate, not at the level of individual gene, but at the level of functionally related gene sets and global molecular phenotypes.

More specifically the course covers :

  • data normalization,
  • sequence alignment for next generation sequencing,
  • selection of differentially expressed genes,
  • gene set analysis,
  • supervised and unsupervised classification of genome-wide expression profiles,
  • typical statistical illusions that come with the above,
  • how to analyze global, large-scale, genotypes and phenotypes with dimensionality reduction.
Computational methods will be introduced together with the research problems drawn mostly from oncology research. Thus, the student will learn for example: to what extent the glogal gene expression varies among different human populations, how to predict cancer outcome from gene expression profile, how to establish connection between drugs and biological conditons from gene expression databases, etc.

Biostatistics

  • The basic principles of the hypothesis tests
  • Using the statistical software jamovi to perform:
    • basics hypothesis tests
    • ANOVA methods
    • multiple regressions
    • a basic survival analysis
  • critical analysis of the methodology of an article

Objectifs (et/ou acquis d'apprentissages spécifiques)

Provide conceptual tools for a critical assessment of the functional genomics literature. Introduction to several important databases and tools.

The student will be able to understand to analyze the statistics of trial data using computer tools and interpret them critically.

Méthodes d'enseignement et activités d'apprentissages

The course does not present a nicely polished textbook view of science, but science in the making with its ectics, turn arounds and controversies. Lectures are interrupted by demonstration of computational methods on real life data.

In the biostatistical course, the student will also have to resolve exercises with the help of the jamovi software.

Contribution au profil d'enseignement

Master in-depth scientific knowledge to understand a problem scientific research and the questions it asks, identify the most relevant experiences and the most appropriate techniques to meet them.

Master the basic scientific techniques of biomedical research that will enable him/her to develop and implement an experimental approach, to compare its results forecasts, and to assess the validity limits of its model. Plan and organize the successive stages of an experimental protocol and validate it.

Use study tools (including bioinformatics tools) in the biomedical sciences and main measuring instruments and to identify sources of errors.

Read the English language scientific literature fluently and search for it relevant.

Present correct and consistent scientific information.

To be able to read, interpret, criticize a scientific article

To question oneself, to be critical, to debate, to debate and / or to defend one's ideas.

Consider ethical issues and apply ethical behavior.

Autres renseignements

Contacts

Vincent.Detours@ulb.be

Campus

Erasme

Evaluation

Méthode(s) d'évaluation

  • Examen écrit

Examen écrit

Construction de la note (en ce compris, la pondération des notes partielles)

3 hours written exam, with 2 hours for bioinformatics, 1 hour for biostatistics

The exam will contain MCQ and open-ended questions.

Mark calculation method (including weighting of intermediary marks)

If grade bioinformatics>8 AND grade biostatistics>8 then

Grade = (Grade bioinformatics)x2/3 + (Grade biostatistics)x1/3

If grade bioinformatics<8 OR grade biostatistics<8 then

Grade = min(grade bioinformatics, grade biostatistics)

This grading algorithm ensures that no student pass while grossly failing one part of the course.

If the overall grade for the course unit is below 10/20, but either the bioinformatics grade or the biostatistics grade is 10/20 or higher, that grade will be carried over from the first session to the second session, but not from one academic year to the next.

No grade below 10/20 will be carried over.

Langue(s) d'évaluation

  • français
  • anglais

Programmes