Jiang Bian, Ph.D., found that TRI has had a positive impact on research at UAMS.

A recent analysis found that TRI has played an important and effective role in promoting collaborative research at UAMS.

Led by Jiang Bian, Ph.D., the social network analysis looked at researcher collaborations based on grant data from 2006 to 2012. UAMS received its Clinical and Translational Science Award (CTSA) in 2009.

Bian’s work has led to new informatics tools for measuring the efficiency of UAMS’ research environment, whether it is improving, and whether external factors are playing a role. The analysis was published in the February 2014 Journal of Biomedical Informatics.

“We found that the CTSA and the establishment of TRI has had a positive impact,” said Bian, a researcher in the Department of Biomedical Informatics whose analysis was supported by TRI. “Prior to the TRI, there were far fewer collaborations and smaller, more isolated groups of researchers.”

Prediction Model
An intriguing element to his work is a statistical model showing which researchers should collaborate. The model was developed using 80 percent of the researcher population and then verified by applying it to the other 20 percent.

“Being able to predict is pretty exciting,” Bian said. “It helps people understand what sort of collaboration environment we have and whether the things we’re doing are enriching the environment for collaboration.”

Bian said TRI will reach out to researchers who are not collaborating but who should be based on the prediction model. “We’ll share our results with them so that they’re aware of the opportunity.”

In addition, Bian is developing visual analytics for TRI. The visualization tool, based on collaborations found in grant data, is designed to help any audience understand the nature of research networks and how they may evolve over time. The tool can track individual UAMS researchers as well as groups of researchers over time.

View Bian’s poster presentation: Interactive visualization for understanding and analyzing biomedical research collaboration networks.