Biotechnology: omics

lsinc1332  2023-2024  Charleroi

Biotechnology: omics
5.00 credits
30.0 h + 30.0 h
Q2

  This learning unit is not open to incoming exchange students!

Teacher(s)
Branders Vincent;
Language
French
Prerequisites
  • Molecular biology
  • Biochemistry
  • Data visualization
  • Statistics

The prerequisite(s) for this Teaching Unit (Unité d’enseignement – UE) for the programmes/courses that offer this Teaching Unit are specified at the end of this sheet.
Main themes
This course will cover the different biological analysis techniques that generate high-throughput data (so-called “omics” techniques), such as: DNA and RNA sequencing, proteomics, metabolomics... (non-exhaustive list which will be adapted according to the rapid evolution of this field).
For each method, the course will introduce:
  •         The operating principle of each method (sequencing, mass spectrometry, etc.)
  •         Analysis, processing and normalization of raw data
  •         Data interpretation and visualization.
  •         The biases and pitfalls related to these techniques (problems of technical and biological variability, reproducibility, experimental design).
Generic methods for analyzing biological data will also be covered (clustering, enrichment, ontologies, etc.), in connection with the data analysis course and the statistics course.
Finally, the course will include an introduction to the databases that can be used in this field (TCGA, GEO, Encode etc).
Learning outcomes

At the end of this learning unit, the student is able to :

  • Understand the operating principle of omics methods
  • Understand the concepts and principles of omics data analysis
  • Analyze simple omics data
  • Understand and critique a publication presenting omics data
 
Content
1. Introduction
2. DNA sequencing (genomics)
  • Principle and technologies available
  • Genome, exome, panel
  • Analysis of raw data (alignment, reference genome, construction of a new genome, calling of variants, quality controls, etc.)
  • Interpretation
3. RNA sequencing (transtriptomics)
  • Principle and technologies
  • Gene expression analysis
  • Variants, mergers, new transcripts
4. Proteomics
  • Mass spectrometry, principle and technologies
  • Data analysis (identification of peptides and proteins, quantification)
  • Data interpretation
Teaching methods
Lectures and guided practical session
  1. Practical sessions are performed in groups to use databases and results interpretation tools
Evaluation methods
The final grade consists of
  • 25% for the continuous evaluation,
  • 75% for the final exam
The continuous evaluation, which consists of assignments, will result in a single overall grade, communicated at the end of the last assignment. Failure to comply with the methodological instructions defined on moodle, in particular with regard to the use of online resources or collaboration between students, for any work/assignment will result in an overall mark of 0 for the continuous assessment.
The continuous assessment grade is fixed at the end of the semester: there is no option to receive a new grade for it during the second session.
The final exam is, by default, a written exam (on paper or, when appropriate, on a computer).
Teaching materials
  • Required teaching material include all documents (lecture slides, project assignments, complements, ...) available from the Moodle website for this course.
  • Les supports obligatoires sont constitués de l'ensemble des documents (transparents des cours magistraux, énoncés des travaux pratiques, compléments, ...) disponibles depuis le site Moodle du cours.
Faculty or entity
SINC


Programmes / formations proposant cette unité d'enseignement (UE)

Title of the programme
Sigle
Credits
Prerequisites
Learning outcomes
Bachelor in Computer Science