Machine Learning Reveals Time-Varying Microbial Predictors with Complex Effects on Glucose Regulation

Author:

Aasmets Oliver12,Lüll Kreete12,Lang Jennifer M.3,Pan Calvin3,Kuusisto Johanna4,Fischer Krista5,Laakso Markku4,Lusis Aldons J.367,Org Elin1ORCID

Affiliation:

1. Institute of Genomics, Estonian Genome Centre, University of Tartu, Tartu, Estonia

2. Department of Biotechnology, Institute of Molecular and Cell Biology, University of Tartu, Tartu, Estonia

3. Department of Medicine, University of California, Los Angeles, California, USA

4. Institute of Clinical Medicine, Internal Medicine, University of Eastern Finland, Kuopio, and Kuopio University Hospital, Kuopio, Finland

5. Institute of Mathematics and Statistics, University of Tartu, Tartu, Estonia

6. Department of Human Genetics, University of California, Los Angeles, California, USA

7. Department of Microbiology, Immunology and Molecular Genetics, University of California, Los Angeles, California, USA

Abstract

Recent studies have shown a clear link between gut microbiota and type 2 diabetes. However, current results are based on cross-sectional studies that aim to determine the microbial dysbiosis when the disease is already prevalent.

Funder

HHS | National Institutes of Health

EMBO

GENTRANSMED and Estonian Center of Genomics/Roadmap II

Academy of Finland

EC | European Regional Development Fund

Eesti Teadusagentuur

Publisher

American Society for Microbiology

Subject

Computer Science Applications,Genetics,Molecular Biology,Modelling and Simulation,Ecology, Evolution, Behavior and Systematics,Biochemistry,Physiology,Microbiology

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