• Heidelberg


Julianus Pfeuffer, Timo Sachsenberg (CIBI)


GCB 2019.

Computational mass spectrometry provides important tools and bioinformatic solutions for the analysis of proteomics data. Different methods for label-free quantification have been developed in recent years and were successfully applied in a wide range of studies. Targeted approaches for label-free quantification, like SWATH-MS, achieve deep proteome coverage over a large number of samples while non-targeted methods have shown great potential in unbiased discovery studies. This de.NBI training event introduces key concepts of both targeted SWATH-MS and non-targeted label-free analysis using workflow-based processing of real-life datasets. We will introduce several open-source software tools for proteomics, primarily focusing on OpenMS (http://www.OpenMS.org). In a hands-on session, we will demonstrate how to combine these tools into complex data analysis workflows including visualization of the results. Participants will have the opportunity to bring their own data and design custom analysis workflows together with instructors. For participants interested in developing their own algorithms and methods within the OpenMS framework, we provide a brief introduction to pyOpenMS – the python interface to the OpenMS development library.
Training material and handouts will be prepared for both users that want to design proteomic workflows, as well as training material for algorithm and tool developers.

Software Requirements:
The participants should bring their own laptop computers. Installer versions of required software will be made available.

LC-MS based proteomics, OpenMS, workflows, KNIME, data analysis

OpenMS/pyOpenMS, KNIME

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