Elhanan Borenstein, Ph.D.

Dept of Genome Sciences
University of Washington

3720 15th Ave NE
Foege Building, S103B
Box 355065
Seattle, WA 98195-5065

Phone: (206) 685-8165
Fax: (206) 685-7301

MIMOSA is a novel algorithm for mechanistically linking microibome ecology and metabolomic data.

» MIMOSA>Code (GitHub)
  Download the MIMOSA source code from GitHub repository.

  Learn how to obtain, compile, and use MIMOSA in your analysis.

Understanding the MIMOSA algorithm

MIMOSAis a comprehensive framework to systematically link variation in metabolomic data with community composition by utilizing taxonomic, genomic, and metabolic information. Specifically, MIMOSA integrates available and inferred genomic data, metabolic network modeling, and a method for predicting community-wide metabolite turnover to estimate the biosynthetic and degradation potential of a given community. It then compares variation in predicted metabolic potential with variation in measured metabolites' abundances to evaluate whether community composition can explain observed shifts in the community metabolome, and to identify key taxa and genes contributing to the shifts.
If you are using MIMOSA please cite the following paper:
Noecker et al., Metabolic model-based integration of microbiome taxonomic and metabolomic profiles elucidates mechanistic links between ecological and metabolic variation. mSystems, 1:1, e00013-15, 2016.