Health and Life Sciences Community of Practice aims to connect computational scientists to subject area researchers in science-related fields

The Computational Health and Life Sciences Community of Practice hosted by TDAI is focused on developing big-data analytics that have translational values and can be deployed in healthcare and life sciences. Shili Lin, Professor of Statistics in the College of Arts and Sciences, along with Xia Ning, Associate Professor of Biomedical Informatics in the College of Medicine and Computer Science and Engineering in the College of Engineering serve as co-directors for this Community of Practice (CoP).

Lin was asked to form and co-direct this Community of Practice about two years ago. The combination of her experience working with researchers in the Wexner Medical Center and her methodological research interests have contributed to setting the goals of this particular CoP. The Community of Practice works to connect the computational community to medical researchers. Lin said, “I’m very glad to see Xia joining the leadership team, as she represents the researchers in our CoP who are from the College of Medicine.”

Some of the goals of the Health and Life Sciences CoP include fostering cross-disciplinary collaborative activities to connect computational scientists to subject area researchers within the health and life sciences domains. Beyond Ohio State, Lin and Ning are also exploring partnerships with other institutions to draw on the expertise of local scientific communities.

Transdisciplinary research is extremely valuable to the success of this Community of Practice. Ning said, “It’s very important to have a common platform for people from both an engineering background and a medical background. Physicians know about different diseases, cancers, and how to care for patients, but they don’t all know how to analyze the data they receive.” The computational scientists in the CoP, including statisticians and bioinformaticians, help physician collaborators at the Wexner Medical Center process and analyze their data.

Not surprisingly, COVID-19 has had an impact on the progression of their research, which includes ongoing work on drug repositioning. “Among all of the FDA approved drugs, we want to find which ones can be used to treat COVID-19,” Ning said. “We use all of the protein, pathway and drug data and we put them into our model to predict which drug is most likely to be effective against COVID-19. We also use a large collection of patient electronic health records (EHR) data to understand the disease course”

“EHR data is incomplete so it requires a huge effort. That’s why it’s important that the computational scientists are collaborating with the medical researchers to prioritize which information they need to understand regarding various health issues,” Lin added.

Lin and Ning hope to strengthen the CoP by getting more medical researchers involved, who can provide more domain-area expertise. Lin said, “This would be a huge help in the coming year with future projects, beyond COVID-19.”

To learn more about the COP or to join, visit the Computational Health and Life Sciences Community of Practice page.

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