Title
Identifying common components across biological network graphs using a bipartite data model.
Document Type
Article
Publication Date
10-13-2014
JAX Source
BMC Proc 2014 Oct 13;8(Suppl 6):S4.
PMID
25374613
Abstract
The GeneWeaver bipartite data model provides an efficient means to evaluate shared molecular components from sets derived across diverse species, disease states and biological processes. In order to adapt this model for examining related molecular components and biological networks, such as pathway or gene network data, we have developed a means to leverage the bipartite data structure to extract and analyze shared edges. Using the Pathway Commons database we demonstrate the ability to rapidly identify shared connected components among a diverse set of pathways. In addition, we illustrate how results from maximal bipartite discovery can be decomposed into hierarchical relationships, allowing shared pathway components to be mapped through various parent-child relationships to help visualization and discovery of emergent kernel driven relationships. Interrogating common relationships among biological networks and conventional GeneWeaver gene lists will increase functional specificity and reliability of the shared biological components. This approach enables self-organization of biological processes through shared biological networks. BMC Proc 2014 Oct 13;8(Suppl 6):S4.
Recommended Citation
Baker, Ej; Culpepper, C; Philips, C; Bubier, Jason A.; Langston, M; and Chesler, Elissa J., "Identifying common components across biological network graphs using a bipartite data model." (2014). Faculty Research 2014. 177.
https://mouseion.jax.org/stfb2014/177