This course provides hands-on training in the basics of mass spectrometry (MS) and proteomics bioinformatics. You will receive training on how to use search engines and post-processing software, quantitative approaches, MS data repositories, the use of public databases for protein analysis, annotation of subsequent protein lists, and incorporation of information from molecular interaction and pathway databases.

The practical elements of the course will take raw data from a proteomics experiment and analyse it. You will be able to go from MS spectra to identifying and quantifying peptides, and finally to obtaining lists of protein identifiers that can be analysed further using a wide range of resources. The final aim is to provide you with the practical bioinformatics knowledge you need to go back to the lab and process your own data when collected.

This course is organised in association with the Vlaams Instituut voor Biotechnologie (VIB, the Flemish Institute for Biotechnology).

Pre-recorded material may be provided before the course starts that you will need to watch, read, or work through to gain the most out of the actual training event.

Who is this course for?
The course is aimed at research scientists with a minimum of a degree in a scientific discipline, including industrial, laboratory and clinical staff, as well as specialists in related fields. Basic knowledge of mass spectrometry experiments for proteomics would be an advantage.
After completing the course, you will be able to:

- Use and summarise bioinformatics tools to analyse shotgun proteomics data, involving identification and quantification approaches
- Browse, search, submit, retrieve, and re-use proteomics data from widely used public proteomics data repositories
- Evaluate the strengths and weaknesses of several experimental and bioinformatics analysis approaches
- Use tools to perform functional annotation of lists of proteins

Course content

- Mass spectrometry basics
- Proteomics bioinformatics basics
- Quantitative proteomics
- Introduction to data independent acquisition approaches
- MS proteomics repositories, including PRIDE and PRIDE-related tools and ProteomeXchange.
-Data re-use of public proteomics datasets.
-Introduction to proteogenomics
-Protein interaction data through IntAct and IMEX resources
-Functional analysis of proteins using Cytoscape and Reactome