Familiarisation with the vocabulary and experimental approaches of high-throughput analysis.
Understanding their potential and limitations.
Acquire a methodology for using and interpreting a proteomic data set.
This course aims to familiarise students with high-throughput analysis techniques, such as metabolomics, lipidomics, proteomics and the applications of high-throughput DNA sequencing. The principles, advantages and limitations of these different approaches will be presented and illustrated by examples/applications.
For Arnould :
External contributors aiming to develop
1) metabolomics based on various aspects of mass spectrometry
2) the use of metabolomics in the context of cancer
3) lipidomics
For the De Bolle part:
Applications arising from the possibility of high-throughput sequencing (Tn-seq, ChIP-seq, RNA-seq, Hi-C, Ribo-seq, CLIP-seq, FAIRE-seq, ATAC-seq)
For the Fox section:
1) Introduction to proteomics
2) Mass spectrometry for protein analysis
3) Protein identification: from spectrum to database
4) Quantitative analysis strategies and examples
1) Introduction and objectives
2) Lipidomics and metabolomics
3) Proteomics
4) Genomics
A proteomic data set is presented to the students. The analysis strategies are explained.
Working in pairs, the students analyse the data set and extract relevant biological information. The assessment is based on the presentation of their results.
Theoretical part :
Oral examination with each holder.
A mark of severe failure in one of the parts (< or equal to 7/20) results in an overall failure of the UE.
The student will only repeat the failed part(s).
Practical part:
Student pairs present the results of their biological analysis of the proteomic data set they have been given.
| Training | Study programme | Block | Credits | Mandatory |
|---|---|---|---|---|
| Bachelier en sciences biologiques | Standard | 0 | 2 | |
| Bachelier en sciences biologiques | Standard | 3 | 2 |