Teaching Computers to Recognize Sick Guts: Machine-Learning and the Microbiome

By Tiffany Fox San Diego, Calif., Jan. 12, 2017 — A new proof-of-concept study by researchers from the University of California San Diego succeeded in training computers to “learn” what a healthy versus an unhealthy gut microbiome looks like based on its genetic makeup. Since this can be done by genetically sequencing fecal samples, the research suggests there is great promise for new diagnostic tools that are, unlike blood draws, non-invasive. A visualization of protein families is projected onto researchers Mehrdad Yazdani and Bryn Taylor in the UC San Diego Center for Microbiome Innovation. Selfie by Bryn Taylor.  As recent advances in scientific understanding of Parkinson’s disease and cancer immunotherapy have shown, our gut microbiomes – the trillions of bacteria, viruses and other microbes that live within us – are emerging as one of…


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