Navlakha, S., Kingsford, C. (November 2010) Exploring biological network dynamics with ensembles of graph partitions. Pac Symp Biocomput. pp. 166-177. ISSN 2335-6928
Abstract
Unveiling the modular structure of biological networks can reveal important organizational patterns in the cell. Many graph partitioning algorithms have been proposed towards this end. However, most approaches only consider a single, optimal decomposition of the network. In this work, we make use of the multitude of near-optimal clusterings in order to explore the dynamics of network clusterings and how those dynamics relate to the structure of the underlying network. We recast the modularity optimization problem as an integer linear program with diversity constraints. These constraints produce an ensemble of dissimilar but still highly modular clusterings. We apply our approach to four social and biological networks and show how optimal and near-optimal solutions can be used in conjunction to identify deeper community structure in the network, including inter-community dynamics, communities that are especially resilient to change, and core-and-peripheral community members.
| Item Type: | Paper |
|---|---|
| Uncontrolled Keywords: | |
| Subjects: | bioinformatics > computational biology > algorithms organs, tissues, organelles, cell types and functions > organs types and functions > brain organs, tissues, organelles, cell types and functions > tissues types and functions > signal transduction |
| CSHL Authors: | |
| Communities: | CSHL labs > Navlakha lab |
| Depositing User: | Matthew Dunn |
| Date: | November 2010 |
| Date Deposited: | 08 Nov 2019 14:32 |
| Last Modified: | 08 Nov 2019 14:32 |
| Related URLs: | |
| URI: | https://repository.cshl.edu/id/eprint/38683 |
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