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Can You Imagine: Visualizing Biomedical Breakthroughs in Data?

Making sense of complex biological data is the daily routine for the VI-Bio group at NCSA. Whether it be investigating the role of certain dietary interventions in the human microbiome, working to improve risk prediction in breast cancer, or even developing an app to connect cancer patients and caregivers, VI-Bio is constantly working to make data more accessible, culminating in visual analytic tools for studying genomic and related data.

What’s not routine about this work, however, are the outcomes: the VI-Bio group applies machine learning approaches to analyze the data and transforms the abstract biological results into visual form.

“We take complex biological data and help researchers make sense of it,” says Senior Research Scientist Colleen Bushell. Identifying relevant features in these data and presenting the complexity in a visual form improves comprehension, she explains, which in turn leads to new discoveries and insights.

The VI-Bio group, which also includes Matt Berry, Peter Groves, Lisa Gatzke, Xiaoxia Liao, Michael Welge, and Loretta Auvil has multiple collaborators, including the Mayo Clinic and Northwestern University. They build professional quality software and apply their design methodology to create interactive data visualizations and complex user interfaces that allow researchers to execute machine learning analysis and study their results.

Several of Vi-Bios projects have led to new insights in human diseases including cancer, chronic pelvic pain, latent tuberculosis, and heart disease.

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