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The function of communities in protein interaction networks at multiple scales
| Content Provider | Open Access Library (OALib) |
|---|---|
| Author | Anna CF Lewis Nick S. Jones Mason A. Porter Charlotte M. Deane |
| Abstract | Our results demonstrate that the functional homogeneity of communities depends on the scale selected, and that almost all proteins lie in a functionally homogeneous community at some scale. We judge functional homogeneity using a novel test and three independent characterizations of protein function, and find a high degree of overlap between these measures. We show that a high mean clustering coefficient of a community can be used to identify those that are functionally homogeneous. By tracing the community membership of a protein through multiple scales we demonstrate how our approach could be useful to biologists focusing on a particular protein.We show that there is no one scale of interest in the community structure of the yeast protein interaction network, but we can identify the range of resolution parameters that yield the most functionally coherent communities, and predict which communities are most likely to be functionally homogeneous.Large protein-protein interaction data sets [1-3] and functional information about many proteins are increasingly available. This allows one to investigate the patterns in protein-protein interactions that enable proteins to act concertedly to carry out their functions. In particular, considerable recent attention has been given to the modularity of the cell's functional organisation [4-6]. A module is often thought of as a group of components that carry out a functional task fairly independently from the rest of the system. It is thought that such modules yield robust and adaptable systems [7]. There is also much suggestive evidence that modules within the cell are themselves the building blocks of a higher level of structural organisation (e.g. [8-10]).Within the networks literature a great many algorithms have been proposed that locate dense regions in a network, often called communities (reviewed in [11,12]). A community is loosely defined as a group of nodes that are more closely associated with themselves than with the |
| ISSN | 17520509 |
| Journal | BMC Systems Biology |
| DOI | 10.1186/1752-0509-4-100 |
| Publisher | BioMed Central |
| Publisher Date | 2010-01-01 |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
| Subject | Applied Mathematics Structural Biology Molecular Biology Modeling and Simulation Computer Science Applications |
