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IBIP22 Integrative Biological Interpretation using ProteomicsDownloadable poster in PDF |
IMPORTANT DATES for this Course
Candidates with adequate profile will be accepted in the next 72 hours after the application until we reach 20 participants. |
Instructors: |
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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. |
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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. |
![]() 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. |
ObjectivesAfter 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-requisitesStrictly speaking, there are no pre-requisites. Prior knowledge that will be useful, but not required:
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Application |
Detailed Program |
Testimonials |
Support
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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 Last updated:May 15th 2022 |