Integrative Biological Interpretation using Proteomics

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   IMPORTANT DATES for this Course
   Deadline for applications: October 30th 2019
   Course date: November 04th - November 07th 2019

Candidates with adequate profile will be accepted in the next 72 hours after the application until we reach 20 participants.


Veit Schwämmle develops and applies computational solutions for improved data analysis in large-scale omics experiments with focus on proteins and their post-translational modifications (PTMs). The aim is to better understand the functional protein states in order to determine, confirm and predict their contribution to cell behavior and disease.
Veit is associate professor and teaches courses in bioinformatics on Bachelor, Master and PhD level. He gives workshops at international conferences and organises European hackathons.

Affiliations: University of Southern Denmark, Odense, DK

Marc Vaudel research focuses on better understanding the interplay between genomics and signalling in metabolic diseases. He is involved in multi-omics research on diabetes and early growth, using large data sets to better characterize the mechanisms underlying diseases. He developed multiple methods and tools for proteomic and genomic data analysis. He is actively involved in genomic consortia and in the handling of large cohort data.
Marc has been involved in multiple GTPB courses in proteomics data analysis. He is regularly providing bioinformatics training in research institutes, and is a guest lecturer at the University of the Faroe islands.

Affiliation: University of Bergen, Bergen, NO

David Bouyssié develops open-source tools for the quantification of peptides and proteins from LC-MS/MS raw data. This includes the creation of algorithms dedicated to the analysis of label-free experiments, such as signal detection, retention time alignment, intensity normalization and data summarization, but also user-friendly graphical interfaces for LC-MS data visualization.
David organizes regularly practical bioinformatics workshops in EuPA congresses, and teaches quantitative proteomics at the University of Toulouse (Master degree).

Affiliation: University of Toulouse, IPBS/CNRS, FR

Course description

Quantitative proteomics by mass spectrometry has become an essential tool for multi-omics studies aiming at answering important biological questions in a system-wide perspective. Proteomics data contain rich and deep information that can become challenging to extract, interpret, and interface with other experimental outcomes.
This training course is aimed at researchers who are not expert in proteomics and want to integrate quantitative proteomics results into wider biomedical experiments. We will focus on quality control from an end-user perspective, link to the underlying genomic context, multivariate analysis, protein complexes investigation, and compare different platforms for biological interpretation.
After the training, participants will be able to critically interpret results, troubleshoot analyses, and will be ready to successfully attend more specialized training e.g. in proteogenomics or biological network analysis.

Course Pre-requisites

Strictly speaking, there are no pre-requisites. Prior knowledge that will be useful, but not required:
  • Acquaintance with bottom-up proteomics workflow (sample preparation, LC-MS, terminology)
  • Basics of quantitative proteomics (labelling vs. label-free, bioinformatics methods to infer peptide and protein abundance)
  • Awareness of protein inference issues in proteomics identification and quantification
  • Basics of scripting in R/Python
This course does not cover the basics of proteomics, proteomics bioinformatics, and large data handling.

Detailed Program

Instituto Gulbenkian de Ciência,

Apartado 14, 2781-901 Oeiras, Portugal

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Last updated:September 29th 2019