| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 429433 | Journal of Computational Science | 2012 | 9 Pages |
Abstract
We propose using a graph-theoretic data structure, the Voronoi diagram for graphs, for analyzing the structure of biological networks. The Voronoi diagram for graphs (VDG) offers an efficient way to cluster the members of a network based on their distance to a subset of input nodes. We study the distance-based decomposition of the human erythrocyte interactome provided by VDG, seeking to elucidate the influence of sickle cell anemia on the function of the erythrocyte proteins. We also provide an efficient open-source Java package that computes VDG.
Related Topics
Physical Sciences and Engineering
Computer Science
Computational Theory and Mathematics
Authors
M. Zivanic, O. Daescu, A. Kurdia, S.R. Goodman,