We accelerate microbiome research
and develop new methods for manipulating microbiomes
to improve human health and benefit the environment.

 

UC San Diego is a world-leader in microbiome research, biomedical engineering, quantitative measurements and modeling, cellular and chemical imaging, drug discovery, "omics" sciences and much more. We draw interdisciplinary teams of these researchers together to push the boundaries of human understanding of microbiomes — the distinct constellations of bacteria, viruses and other microorganisms that live within and around humans, other species and the environment.

 

Learn more about the microbiome center (web) »

Learn more about the microbiome center (brochure) »

 

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Recent News


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Jun 30, 2020

Center for Microbiome Innovation names Dr. Andrew Bartko as Executive Director.

UC San Diego Center for Microbiome Innovation names Dr. Andrew Bartko, a veteran research leader from Battelle Memorial Institute, as its new Executive Director. Bartko embarks on new role as founding executive director Dr. Sandrine Miller-Montgomery departs to lead Micronoma, a San Diego-based startup spawned out of the Center.


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May 4, 2020

UC San Diego Researchers Optimize Microbiome Tool for Computer GPUs.

Researchers at the University of California San Diego have been applying their high-performance computing expertise by porting the popular UniFrac microbiome tool to graphic processing units (GPUs) in a bid to increase the acceleration and accuracy of scientific discovery, including urgently needed COVID-19 research.

“Our initial results exceeded our most optimistic expectations,” said Igor Sfiligoi, lead scientific software developer for high-throughput computing at the San Diego Supercomputer Center (SDSC) at UC San Diego. “As a test we selected a computational challenge that we previously measured as requiring some 900 hours of time using server class CPUs, or about 13,000 CPU core hours. We found that it could be finished in just 8 hours on a single NVIDIA Tesla V100 GPU, or about 30 minutes if using 16 GPUs, which could reduce analysis runtimes by several orders of magnitude. A workstation-class NVIDIA RTX 2080TI would finish it in about 12 hours.”


   

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