The Voronoi diagram for graphs and its application in the Sickle Cell Disease research

M. Zivanic, O. Daescu, A. Kurdia, Steven Goodman

Research output: Contribution to journalArticle

3 Citations (Scopus)

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.

Original languageEnglish (US)
Pages (from-to)335-343
Number of pages9
JournalJournal of Computational Science
Volume3
Issue number5
DOIs
StatePublished - Sep 1 2012
Externally publishedYes

Fingerprint

Voronoi Diagram
Data structures
Decomposition
Proteins
Cell
Graph in graph theory
Erythrocyte
Biological Networks
Open Source
Java
Data Structures
Protein
Decompose
Subset
Vertex of a graph

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)
  • Modeling and Simulation

Cite this

The Voronoi diagram for graphs and its application in the Sickle Cell Disease research. / Zivanic, M.; Daescu, O.; Kurdia, A.; Goodman, Steven.

In: Journal of Computational Science, Vol. 3, No. 5, 01.09.2012, p. 335-343.

Research output: Contribution to journalArticle

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