Proteomics Data Analysis

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IMPORTANT DATES for this Course
Deadline for applications: March 25th 2019
Course date: April 1st - April 5th 2019

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


Lennart Martens Lennart Martens is Full Professor of Systems Biology at Ghent University, group leader of the Computational Omics and Systems Biology (CompOmics) group at VIB, and Associate Director of the VIB-UGent Center for Medical Biotechnology, all in Ghent, Belgium. He has been working in proteomics bioinformatics since his Master’s degree, which focused on the computational interpretation of peptide mass spectra. He then worked as a software developer and framework architect for a software company for a few years, before returning to Ghent University to pursue a Ph.D. focused on proteomics and proteomics informatics. During this time, he worked on the development of high-throughput peptide centric proteomics techniques and on bioinformatics tools to support these new approaches. In 2003 he started the PRIDE proteomics database at the EBI as a Marie Curie fellow of the European Commission. After obtaining his Ph.D., he rejoined the PRIDE group at EBI, which he coordinated for several years before moving back to Ghent University to take up his current position. Prof. Martens has been elected to the Human Proteome Organisation (HUPO) Council in 2016, and to the HUPO Executive Board in 2017. He received the 2014 Prometheus Award for Research Excellence from Ghent University, and the 2015 ‘Juan Pablo Albar’ Proteomics Pioneer Award from the European Proteomics Association. An author on more than 200 peer-reviewed papers, he has also co- written two popular Wiley textbooks: Computational Methods for Mass Spectrometry Proteomics (ISBN: 978-0-470-51297-5), and Computational and Statistical Methods for Protein Quantification by Mass Spectrometry (ISBN: 978-1-119-96400-1).

Affiliation: Ghent University and VIB, Ghent, BE

Harald Barsnes is a group leader at both the Computational Biology Unit at the Department of Informatics and at the Proteomics Unit at the Department of Biomedicine, both at the University of Bergen, Norway. The main focus of his group is the development of user-friendly open-source bioinformatics tools that enable and empower researchers to analyse and share their own data. His research has resulted in numerous publications and a long list of freely available proteomics software, e.g., PeptideShaker, SearchGUI and PRIDE Converter. Barsnes has also been a guest editor in PROTEOMICS and has co-authored a Wiley text book called 'Computational and Statistical Methods for Protein Quantification by Mass Spectrometry'. In 2015 he received the Meltzer Award for Excellent Young Researchers at the University of Bergen, and in 2016 he was awarded a prestigious recruitment fellowship from the Bergen Research Foundation.

Affiliation: Department of Biomedicine and Department of Informatics, University of Bergen, NO

Lieven Clement is an Associate Professor of Statistical Genomics at Ghent University. He is an expert in developing statistical methods and open source tools for differential omics data analysis. His research efforts resulted in numerous publications on novel methods and tools for, and applied research in omics data analysis. His lab is built around three strategic research pillars each connected to an omics domain: metagenomics, transcriptomics and proteomics and he also has a strong interest in leveraging his expertise to translational research. He also serves as a member of the core team that established a new Master of Science in Bioinformatics at Ghent University, as a board member of the Belgian Proteomics Association, as an expert in genomics projects of the Belgian Health Care Knowledge Center (KCE), and as an Associate Editor for the journal Biometrics (2011-2017).

Affiliation: Ghent University and VIB, Ghent, BE

Course description

Mass spectrometry based proteomic experiments generate ever larger datasets and, as a consequence, complex data interpretation challenges. In this course, the concepts and methods required to tackle these challenges will be introduced, covering peptide and protein identification, quantification, and differential analysis. Moreover, more advanced experimental designs and blocking will also be introduced. The core focus will be on shotgun proteomics data, and quantification using label-free precursor peptide (MS1) ion intensities. The course will rely exclusively on free and user-friendly software, all of which can be directly applied in your lab upon returning from the course. You will also learn how to submit data to PRIDE/ProteomeXchange, which is a common requirement for publication in the field, and how to browse and reprocess publicly available data from online repositories. The course will thus provide a solid basis for beginners, but will also bring new perspectives to those already familiar with standard data interpretation procedures in proteomics. Note: This is a highly interactive course. It requires that the participants interact with each other and with the course instructors, in order to reach the learning outcomes in full.

Course Pre-requisites

The participants should have a basic knowledge about mass spectrometry based proteomics. Experience in analysing proteomics data is an advantage, but not mandatory. The course does not require advanced computer skills.

You will also be requested to watch the following videos before attending the course:

Detailed Program

Instituto Gulbenkian de Ciência,

Apartado 14, 2781-901 Oeiras, Portugal

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Last updated:Feb 18th 2019