Educators:
Oliver Kohlbacher, Knut Reinert, Julianus Pfeuffer, Timo Sachsenberg, Oliver Alka (CIBI)
Date:
September 25th – 27th 2017
Location:
Tutorial Session (September 25th) and Talks (September 26th – 27th) at the Martin-Luther University, Steintor-Campus, Room SR7, Emil-Abderhalden-Straße, 06108 Halle, Germany
Contents:
We are happy to announce the 10th OpenMS User Meeting on 25. September (09:00) until 27. September 2017 (16:00) at Martin-Luther University.
Note: OpenMS, MetFrag, and SeqAn are developed by the Center for Integrative Bioinformatics (CIBI) and funded as a project of the german network for bioinformatic infrastructure (de.NBI). Thus, for the first time, the OpenMS user meeting is part of a larger CIBI user meeting. Participants may select if they want to participate in the OpenMS or SeqAn track. We also offer a dedicated track for users that want to develop computational tools with OpenMS and SeqAn as well as an introduction to MetFrag.
During the meeting, we will present the capabilities of CIBI tools OpenMS, MetFrag and SeqAn, and discuss your needs and future directions in mass spectrometry and sequence analysis.
This year’s meeting will include an optional OpenMS tutorial session on the first day (Monday, September 25) with the general conference starting on Tuesday, September 26.
Traditionally, the schedule of our meetings is very flexible, allowing discussions and contributions from the participants.
You can bring your data, a wish list, ideas for collaboration projects, and also give a talk about your project. This may include suggestions in areas where currently available software solutions were unsatisfactory. We would be very happy to welcome you in Halle this year.
Keynote speakers:
We are excited to have Keynote talks by Wolfram Weckwerth (MOSYS, Uni Vienna), Greg Landrum (RDKIT/KNIME), Ivo Grosse (MLU Halle), and Steffen Neumann (IPB Halle).
CIBI speakers:
Oliver Kohlbacher, Knut Reinert, Julianus Pfeuffer, Oliver Alka, Timo Sachsenberg
Learning goals:
Capabilities of the OpenMS library and tools; How these tools are combined in flexible and powerful workflows in order to analyze LC-MS based, high-throughput metabolomic and proteomic data; How the powerful workflow engine KNIME is employed to build these workflows, perform statistical analysis and visualize results.
Prerequisites:
Basic to expert level knowledge of MS-based proteomics or metabolomics
Keywords:
LC-MS-based proteomics and metabolomics, OpenMS, workflows, KNIME, data analysis
Tools:
OpenMS, KNIME
Contact:
Scientific and program questions:
Please register at: http://www.openms.org/um2017/