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PaSER powered data streams for real-time processing and feedback
EP38463
Poster Title: PaSER powered data streams for real-time processing and feedback
Submitted on 09 Mar 2022
Author(s): Tharan Srikumar1, Sven Brehmer2, Vijayaraja Gnanasambandan3, Marc- Antoine Beauvais4, Christopher Adams 4, Dennis Trede2, Robin Park4
Affiliations: 1) Bruker Ltd., Milton, ON 2) Bruker Daltonics GmbH & Co.KG, Bremen, Germany 3) Bruker Scientific LLC, Billerica, MA 4) Bruker Scientific LLC, San Jose, CA
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Poster Information
Abstract: Parallel search engine in real-time or PaSER was developed together with the Yates lab to take advantage of GPU-powered database search. The GPU-powered ProLuCID-4D algorithm can process a large number of MSMS spectra generated by the PASEF process on the timsTOF platform, while utilizing all four dimensions – retention time, CCS value, m/z and fragment spectra – to increase the confidence in each identification. PaSER has now been extended into a platform that can integrate 3rd party tools enabling these tools to perform real-time analysis with generally minor adaption of their existing code. To achieve this, PaSER utilizes the concept of streams and stream processors to realize fully customizable real-time processing workflows including on-the fly decision making based on the data being generated.Summary: Parallel search engine in real-time or PaSER was developed together with the Yates lab to take advantage of GPU-powered database search. The GPU-powered ProLuCID-4D algorithm can process a large number of MSMS spectra generated by the PASEF process on the timsTOF platform, while utilizing all four dimensions – retention time, CCS value, m/z and fragment spectra – to increase the confidence in each identification. Report abuse »
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