Improving confidence in lipidomic annotations by incorporating empirical ion mobility regression analysis and chemical class prediction.

Journal: Bioinformatics (Oxford, England)
PMID: 35561172

Abstract

MOTIVATION: Mass spectrometry-based untargeted lipidomics aims to globally characterize the lipids and lipid-like molecules in biological systems. Ion mobility increases coverage and confidence by offering an additional dimension of separation and a highly reproducible metric for feature annotation, the collision cross-section (CCS).

Authors

  • Bailey S Rose
    Department of Chemistry, Center for Innovative Technology, Vanderbilt-Ingram Cancer Center, Vanderbilt Institute of Chemical Biology, Vanderbilt Institute for Integrative Biosystems Research and Education, Vanderbilt University, Nashville, TN 37235, USA.
  • Jody C May
    Department of Chemistry, Center for Innovative Technology , Vanderbilt University , Nashville , Tennessee 37235 , United States.
  • Jaqueline A Picache
    Department of Chemistry, Center for Innovative Technology, Vanderbilt Institute of Chemical Biology, Vanderbilt Institute for Integrative Biosystems Research and Education, Vanderbilt-Ingram Cancer Center, Vanderbilt University, Nashville, Tennessee 37235, United States.
  • Simona G Codreanu
    Department of Chemistry, Center for Innovative Technology, Vanderbilt-Ingram Cancer Center, Vanderbilt Institute of Chemical Biology, Vanderbilt Institute for Integrative Biosystems Research and Education, Vanderbilt University, Nashville, TN 37235, USA.
  • Stacy D Sherrod
    Department of Chemistry, Center for Innovative Technology, Vanderbilt-Ingram Cancer Center, Vanderbilt Institute of Chemical Biology, Vanderbilt Institute for Integrative Biosystems Research and Education, Vanderbilt University, Nashville, TN 37235, USA.
  • John A McLean
    Department of Chemistry, Center for Innovative Technology , Vanderbilt University , Nashville , Tennessee 37235 , United States.

Keywords

External Resources

Popular Topics
Recent Journals