Biological network comparison using graphlet degree distribution
University of California, Irvine
Abstract
MOTIVATION: Analogous to biological sequence comparison, comparing cellular networks is an important problem that could provide insight into biological understanding and therapeutics. For technical reasons, comparing large networks is computationally infeasible, and thus heuristics, such as the degree distribution, clustering coefficient, diameter, and relative graphlet frequency distribution have been sought. It is easy to demonstrate that two networks are different by simply showing a short list of properties in which they differ. It is much harder to show that two networks are similar, as it requires demonstrating their similarity in all of their exponentially many properties. Clearly, it is computationally…
Citation impact
- FWCI
- 7.67
- Percentile
- 100%
- References
- 46
Authors
1Topics & keywords
- Heuristics
- Degree (music)
- Measure (data warehouse)
- Degree distribution
- Computer science
- Similarity (geometry)
- Biological network
- Clustering coefficient