Department of Mathematical Sciences
Sandra Kingan, Brooklyn College and the Graduate Center, CUNY
Tuesday, April 7th, 2026
2:00PM-2:50PM
Stratton Hall 311
Speaker: Sandra Kingan, Brooklyn College and the Graduate Center, CUNY
Title: Centrality Measures in Biological Networks
Abstract: Centrality measures quantify the importance of vertices in a network. In this talk, I will discuss two biological settings in which centrality plays a useful role. The first comes from epidemic modeling, where the spectral properties of a contact network help predict whether an infection will die out or persist. The largest eigenvalue of the adjacency matrix governs threshold behavior for disease spread, motivating a new centrality measure that we call spread centrality. It captures the effect of removing a vertex on the network’s capacity to sustain an epidemic. The second comes from the analysis of bipartite gene-entity networks arising in studies of Alzheimer’s disease, where classical measures such as degree, closeness, and betweenness rankings help identify prominent pathways. Together, these projects illustrate how graph-theoretic centrality provides a useful mathematical lens for understanding biological systems at very different scales. This is joint work with my undergraduate research students Vadym Cherniavskyi, Lea Choe, Gabriel Dennis, Ben Khal, Ravi Kingan, and Alana Marzigliano.