Duggal, Geet, Navlakha, Saket, Girvan, Michelle, Kingsford, Carl (July 2010) Uncovering Many Views of Biological Networks Using Ensembles of Near-Optimal Partitions. MultiClust: 1st International Workshop on Discovering, Summarizing and Using Multiple ClusteringsHeld in Conjunction with KDD-2019.
Abstract
Densely interacting regions of biological networks often correspond to functional modules such as protein complexes. Most algorithms proposed to uncover modules, however, produce one clustering that only reveals a single view of how the cell is organized. We describe two new methods to find ensembles of provably near-optimal modularity partitions that lie within a heuristically constrained search space. We also show how to count the number of solutions in this space that exist within a bounded modularity range. We apply our algorithms to a protein interaction network for S. cerevisiae and show how fine-grained differences between near-optimal partitions can be used to define robust communities. We also propose a technique to find structurally diverse nearoptimal solutions and show that these different partitions are enriched for different biological functions. Our results indicate that near-optimal solutions can represent alternative and complementary views of the network's structure.
| Item Type: | Paper |
|---|---|
| Subjects: | bioinformatics > genomics and proteomics > design > protein network design bioinformatics > computational biology > algorithms organism description > yeast |
| CSHL Authors: | |
| Communities: | CSHL labs > Navlakha lab |
| Depositing User: | Matthew Dunn |
| Date: | July 2010 |
| Date Deposited: | 08 Nov 2019 14:37 |
| Last Modified: | 08 Nov 2019 14:37 |
| Related URLs: | |
| URI: | https://repository.cshl.edu/id/eprint/38682 |
Actions (login required)
 |
Administrator's edit/view item |