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Shannon Quinn

Shannon Quinn
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Assistant Professor

We study and develop in silico methods for quantifying spatiotemporal phenomena in the context of improving public health. This takes several forms: high-throughput image analysis of GFP-tagged z-stacks, machine learning to detect ciliary motion abnormalities in high-speed videomicroscope data, or applied statistics to predict and identify disease outbreaks.

Research Interests:

systems biology, bioimage analysis, data science

Other Affiliations:

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Associate Head: 

Dr. Cordula Schulz, 706-542-3515

Main office phone: 706-542-3310

Fax: 706-542-4271

Head of the Department: Dr. Dennis Kyle