Proteomics Data Analysis

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   IMPORTANT DATES for this Course
   Deadline for applications: Feb 25th 2017 (New)
   Course date: March 6th - March 10th 2017

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 professor of systems biology at Ghent University, and group leader of the Computational Omics and Systems Biology (CompOmics) group at VIB, both 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 served as the chair of the ABRF iPRG in 2011, sits on the Board of DELSA (http://www.delsaglobal.org), the Royal Flemish Society for Chemistry - Proteomics, and the Belgian Proteomics Association. He serves as Academic Editor for PLoS ONE and Open Proteomics and holds Editorial Board positions at PROTEOMICS, BBA Proteins and Proteomics and Molecular BioSystems. An author on more than 135 peer-reviewed papers and has 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 analyze 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

Astrid Guldbrandsen is a postdoc at the Proteomics Unit at the University of Bergen in Norway. She received her PhD at the same institution in 2016, with a project focusing on cerebrospinal fluid (CSF) protein biomarkers for multiple sclerosis (MS) and the development of the online database CSF Proteome Resource CSF-PR. CSF-PR was developed to display protein quantitative data from CSF proteomics studies in an interactive and user-friendly way, and the resource focuses on MS, Alzheimer's and Parkinson's disease studies. She has extensive practical experience from proteomics wet lab experiments, including various labelling and enrichment methods, as well as the use of proteomics data analysis tools such as Skyline, Proteome Discoverer, Byonic, SearchGUI, PeptideShaker and Reporter.

Affiliation: Department of Biomedicine, University of Bergen, NO

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 both protein identification and quantification. The core focus will be on shotgun proteomics data. Quantification through isobaric labels (iTRAQ, TMT) and label-free precursor peptide (MS1) ion intensities will also be introduced. The course will rely exclusively on free and user-friendly software, all of which can be directly applied in your lab upon your return from the course.

An introduction to available online resources and repositories will also be given. Here you will see how to link the results from proteomic experiments with external data to conduct pathway, gene ontology and interaction analyses.
In the course, you will also learn how to submit data to the ProteomeXchange online repositories, and how to browse and reprocess publicly available data from these repositories.

The course will provide a solid basis for beginners, but also 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.

Detailed Program

Instituto Gulbenkian de Ciência,

Apartado 14, 2781-901 Oeiras, Portugal

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Last updated:  Feb 9th 2017