The evolution of biomedical research grant collaborations (BRGC) across time (2006, 2009) and hierarchically related scales (Staff, Department) at the University of Arkansas for Medical Sciences (UAMS) is investigated using network abstractions. This baseline study is a part of the Clinical Translational Science Award (CTSA) efforts in promoting team science and exploring network science approaches for CTSA evaluation. The BRGC data were retrieved from the internally developed grants management system (Automated Research Information Administrator, ARIA). Our analysis revealed the BRGC networks to be disconnected with mutually exclusive research clusters. However, a dominant weakly-connected cluster with positively skewed degree centrality and betweenness distribution was observed across scales and time. Variation in the centrality measures, clustering coefficient, and the impact of perturbing the most-influential nodes as a function of time and scale is investigated. The results presented provide novel insights into the complex nature of BRGC networks that may persist across similar settings.
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