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�Ӱ���Ƶ researchers team up with Cleveland Clinic to track how coronavirus spreads, where strains originate

A team of Cleveland Clinic and �Ӱ���Ƶ researchers is analyzing COVID-19 patient data to better understand how the virus spreads and where various strains originate.

Supported by a , the team is conducting an epidemiologic analysis using data from patient samples collected at Cleveland Clinic.

The work will be led by �Ӱ���Ƶ researcher , interim chair of the computer and data sciences department at the Case School of Engineering, and , a specialist in the Center for Pediatric Infectious Disease at Cleveland Clinic.

Li and Esper will sequence the genome from about 400 of the 2,000 samples to study mutations and use computational algorithms to mine patterns from the genetic sequences.

is the process for determining the order of the DNA nucleotides, or bases, which make up an organism’s DNA—or, in this case, the RNA of the novel coronavirus, SARS-CoV-2. Once the “letters” of the sequence are determined, computational algorithms can be used to mine patterns from the sequences. 

Coupled with epidemiologic data from each affected individual, such as demographic information and diagnosis date, the information will provide new insights into transmission patterns of the novel coronavirus, SARS-CoV-2.

Li’s research specialties are in computational biology and bio-informatics;  data mining and data analytics; and algorithms.

For more information, contact Mike Scott at mike.scott@case.edu.