IBIP19 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: |
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. |
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. |
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. |
Course descriptionQuantitative 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-requisitesStrictly speaking, there are no pre-requisites. Prior knowledge that will be useful, but not required:
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Detailed Program |
Instituto Gulbenkian de Ciência, Apartado 14, 2781-901 Oeiras, Portugal Last updated:September 29th 2019 |