Node similarity within subgraphs of protein interaction networks

Details Node similarity within subgraphs of protein interaction networks Node similarity within subgraphs of protein interaction networks

2007-07-13

arxiv.org/abs/0707.2076v2

Biology

Quantitative Biology

Molecular Networks

10 pages, 5 figures. Edited for typos, clarity, figures improved for readability

Scientific paper

10.1016/j.physa.2008.02.043

We propose a biologically motivated quantity, twinness, to evaluate local similarity between nodes in a network. The twinness of a pair of nodes is the number of connected, labeled subgraphs of size n in which the two nodes possess identical neighbours. The graph animal algorithm is used to estimate twinness for each pair of nodes (for subgraph sizes n=4 to n=12) in four different protein interaction networks (PINs). These include an Escherichia coli PIN and three Saccharomyces cerevisiae PINs -- each obtained using state-of-the-art high throughput methods. In almost all cases, the average twinness of node pairs is vastly higher than expected from a null model obtained by switching links. For all n, we observe a difference in the ratio of type A twins (which are unlinked pairs) to type B twins (which are linked pairs) distinguishing the prokaryote E. coli from the eukaryote S. cerevisiae. Interaction similarity is expected due to gene duplication, and whole genome duplication paralogues in S. cerevisiae have been reported to co-cluster into the same complexes. Indeed, we find that these paralogous proteins are over-represented as twins compared to pairs chosen at random. These results indicate that twinness can detect ancestral relationships from currently available PIN data.

Affiliated with

Also associated with

No associations

Rating

Node similarity within subgraphs of protein interaction networks does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Node similarity within subgraphs of protein interaction networks, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Node similarity within subgraphs of protein interaction networks will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFWR-SCP-O-61135