Utilizing Machine Learning Approaches to Understand the Interrelationship of Diet, the Human Gastrointestinal Microbiome, and Health

By Heather M. Guetterman, L. Auvil, Nate Russell, M. Welge, M. Berry, Lisa Gatzke, C. Bushell, H. Holscher. 2016

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A growing body of literature supports the ability of specific foods and nutrients to impact the gastrointestinal microbiome. However, there is a dearth of knowledge on the interplay of dietary components (e.g. foods and nutrients), gastrointestinal bacteria, and bacterial metabolites. Current analytical approaches limit investigation of these complex interrelations; therefore, further research utilizing modern machine learning methods is needed.

Subfields: Molecular Biology, Physiology, Public Health, Environmental and Occupational Health