Abstract
We describe an approach to clustering the yeast protein-protein inter-action network in order to identify functional modules, groups of proteins forming multi-protein complexes accomplishing various functions in the cell. We have developed a clustering method that accounts for the small-world nature of the network. The algorithm makes use of the concept of k-cores in a graph, and employs recursive spectral clustering to compute the functional modules. The computed clusters are annotated using their protein memberships into known multi-protein complexes in the yeast. We also dissect the protein interaction network into a global subnetwork of hub proteins (connected to several clusters), and a local network consisting of cluster proteins.
| Original language | English |
|---|---|
| Title of host publication | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
| Pages | 265-276 |
| Number of pages | 12 |
| DOIs | |
| State | Published - 2005 |
| Externally published | Yes |
Publication series
| Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
|---|---|
| Volume | 3695 LNBI |
| ISSN (Print) | 0302-9743 |
| ISSN (Electronic) | 1611-3349 |
ASJC Scopus subject areas
- Theoretical Computer Science
- General Computer Science
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