Exploring biological network dynamics with ensembles of graph partitions

Navlakha, S., Kingsford, C. (November 2010) Exploring biological network dynamics with ensembles of graph partitions. Pac Symp Biocomput. pp. 166-177. ISSN 2335-6928

URL: https://www.ncbi.nlm.nih.gov/pubmed/19908369
DOI: 10.1142/9789814295291_0019


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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