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Guidelines for Interpreting Metabolomic Data

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  October 3, 2019

  8:00 a.m. PDT, 11:00 a.m. EDT, 16:00 BST, 17:00 CEST

 

Overview

 

In a typical metabolomics experiment performed with liquid chromatography/mass spectrometry, it is common to detect thousands of signals with unique m/z values from a biological sample. Understanding these data is difficult and often recognized as the rate-limiting step of metabolomics. Although the challenge may seem to be primarily an informatic problem, experimental variables also significantly complicate data interpretation. In this talk, a critical perspective of factors contributing to the complexity of metabolomic data will be presented. Opportunities using intelligent MS acquisition and benchmarking strategies to reduce the analysis burden will be outlined. Guidelines for accurately assessing metabolism from metabolomic datasets and complementary biochemical assays will be discussed.

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Key Learning Objectives

  • Challenges associated with mass spectrometry-based metabolomics
  • The difference between features, compounds, metabolites, and unknowns
  • Emerging workflows to improve interpretation of untargeted metabolomic data

Who Should Attend

  • Metabolism researchers or mass spectrometrists who are new to the field of metabolomics
  • Practitioners of metabolomics interested in data-analysis strategies
  • Scientists interested in global profiling of small molecules, including drugs, pesticides, environmental exposures, etc.
 

Speaker

Dr Gary J. Patti, Ph. D
Associate Professor of Chemistry,
Washington University School of Medicine
 

Moderator

Jeff Huber
Contributing Editor,
C&EN Media Group
 

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