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Next-Generation Plasma Lipidomics: Quantification With dia-PASEF

RECORD | Already taken place We, 8.5.2024
This webinar explores a new workflow for lipidomics using dia-PASEF – a mass spectrometry approach that allows for faster, more comprehensive analysis.
Go to the webinar
Technology Networks: Next-Generation Plasma Lipidomics: Quantification With dia-PASEF
Technology Networks: Next-Generation Plasma Lipidomics: Quantification With dia-PASEF

Human blood plasma contains thousands of distinct lipid species. These lipids can provide new insights into health and disease, with lipidomic profiling revealing new biomarkers for various conditions and being used to monitor the efficacy of treatments.

This webinar explores a new workflow for lipidomics using dia-PASEF – a mass spectrometry approach that allows for faster, more comprehensive analysis. Our expert speaker will show how this method increases lipid library coverage by 60% and allows you to capture complete lipid data in a single run. They will also unveil the optimal approach for high-throughput lipid analysis in human plasma, helping you to enhance your lipidomics research.

Attend this webinar to:

  • Increase your lipid library coverage with dia-PASEF
  • Hear how to gain complete lipid data in a single run
  • Discover an optimized analysis scheme for high-throughput lipidomics

Presenter: Dr. Hannes Röst (Assistant Professor and Canada Research Chair in Mass Spectrometry-Based Personalized Medicine at University of Toronto)

I am a bioinformatics researcher interested in high-throughput technologies that allow us to study the molecular phenotype of a biological system comprehensively. I have worked on theoretical questions in targeted proteomics, contributed to the development of SWATH-MS and wrote the first software capable of targeted analysis of SWATH-MS data in high throughput. I studied at ETH Zurich, Switzerland, worked with Ruedi Aebersold during my PhD and I am now working with Mike Snyder at Stanford University to apply mass spectrometry in a personalized medicine context.

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