Integrative Biological Interpretation using Proteomics

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IMPORTANT DATES for this Course
Deadline for applications: June 15th 2022
Course date: June 20th - June 24th 2022

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

Nadezhda Doncheva researches in the area of network biology and is particularly interested in the integration, analysis and visualization of omics data towards a more comprehensive understanding of diseases. She has been actively involved in the development and maintenance of several computational resources, in particular, the stringApp for Cytoscape, which facilitates the interpretation of proteomics data. Nadezhda teaches regularly about network biology methods and tools at various university courses in Copenhagen as well as at internationally organized courses and conference workshops.

Affiliation: NNF Center for Protein Research, University of Copenhagen, Copenhagen, DK

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 or Python


Detailed Program



The Oeiras Valley support allows us to waive 50% of the course fee to accepted candidates that reside or work in the Oeiras council.

Instituto Gulbenkian de Ciência,

Apartado 14, 2781-901 Oeiras, Portugal

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Last updated:May 15th 2022