Modeling interactome: scale-free or geometric?
University of Toronto · University Health Network · +1 more institution
Abstract
One example of large and complex networks involves protein-protein interaction (PPI) networks. We analyze PPI networks of yeast Saccharomyces cerevisiae and fruitfly Drosophila melanogaster using a newly introduced measure of local network structure as well as the standardly used measures of global network structure. We examine the fit of four different network models, including Erdos-Renyi, scale-free and geometric random network models, to these PPI networks with respect to the measures of local and global network structure. We demonstrate that the currently accepted scale-free model of PPI networks fails to fit the data in several respects and show that a random geometric model provides a much more accurate model of the PPI data. We hypothesize that only the noise in these networks is scale-free.
We systematically evaluate how well-different network models fit the PPI networks. We show that the structure of PPI networks is better modeled by a geometric random graph than by a scale-free model. SUPPLEMENTARY INFORMATION: Supplementary information is available at http://www.cs.utoronto.ca/~juris/data/data/ppiGRG04/
Citation impact
- FWCI
- 5.79
- Percentile
- 100%
- References
- 58
Authors
3Topics & keywords
- Computer science
- Interactome
- Geometric networks
- Random graph
- Network model
- Scale (ratio)
- Complex network
- Scale-free network