Predicting network activity from high throughput metabolomics

PLoS Comput Biol. 2013;9(7):e1003123. doi: 10.1371/journal.pcbi.1003123. Epub 2013 Jul 4.


The functional interpretation of high throughput metabolomics by mass spectrometry is hindered by the identification of metabolites, a tedious and challenging task. We present a set of computational algorithms which, by leveraging the collective power of metabolic pathways and networks, predict functional activity directly from spectral feature tables without a priori identification of metabolites. The algorithms were experimentally validated on the activation of innate immune cells.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't
  • Validation Study

MeSH terms

  • Algorithms
  • Humans
  • Immunity, Innate
  • Mass Spectrometry
  • Metabolomics*