We study what human-associated microbial communities (the “microbiome”) tell us about their host and how they affect its health. We aim to develop personalized microbiome-based and -guided therapeutics and diagnostics.

We do so by examining the sum of microbial species, genes, metabolites and other microbial factors, and studying how they act in tandem, and along with other host factors, to reflect or affect health and disease.

We are ...

… developing data analysis methods that go beyond microbiome composition (who the microbes are) and examine microbiome activity (what the microbes do) directly from human microbiome data.

… studying microbial metabolism, pursuing potentially causal or mechanistic insights by applying optimization methods that incorporate biochemical knowledge (knowledge-driven approaches) and machine learning methods that decipher the metabolic network structure directly from data (data-driven approaches).

… aspiring to develop personally-tailored therapies that act through the microbiome (microbiome-based therapeutics) or to use the microbiome in order to personalize healthcare (microbiome-guided medicine).

... applying our methodology in diverse clinical settings, with a special focus on the reproductive system.

Recent news

New preprint out!

Tuesday, February 2, 2021

Accurate and robust inference of microbial growth dynamics from metagenomic sequencing

New paper out!

Wednesday, November 11, 2020

A reference map of potential determinants for the human serum metabolome

Welcome Aviya!

Monday, October 26, 2020

Aviya Litman joined the lab for a research project as a Data Science Institute (DSI) Scholar.

Welcome Linrui!

Monday, September 21, 2020

Linrui Tang joined the lab for her MA project.