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Not all scale-free networks are born equal: the role of the seed graph in PPI network evolution.

Hormozdiari F, Berenbrink P, Przulj N, Sahinalp SC - PLoS Comput. Biol. (2007)

Bottom Line: The (asymptotic) degree distributions of the best-known "scale-free" network models are all similar and are independent of the seed graph used; hence, it has been tempting to assume that networks generated by these models are generally similar.In this paper, we observe that several key topological features of such networks depend heavily on the specific model and the seed graph used.Furthermore, we show that starting with the "right" seed graph (typically a dense subgraph of the protein-protein interaction network analyzed), the duplication model captures many topological features of publicly available protein-protein interaction networks very well.

View Article: PubMed Central - PubMed

Affiliation: School of Computing Science, Simon Fraser University, Burnaby, British Columbia, Canada.

ABSTRACT
The (asymptotic) degree distributions of the best-known "scale-free" network models are all similar and are independent of the seed graph used; hence, it has been tempting to assume that networks generated by these models are generally similar. In this paper, we observe that several key topological features of such networks depend heavily on the specific model and the seed graph used. Furthermore, we show that starting with the "right" seed graph (typically a dense subgraph of the protein-protein interaction network analyzed), the duplication model captures many topological features of publicly available protein-protein interaction networks very well.

Show MeSH
Comparison of Duplication (Blue) and Preferential Attachment (Green) with 50% Bait and 50% Edge Coverage against the CORE Yeast PPI Network (Red)
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pcbi-0030118-g006: Comparison of Duplication (Blue) and Preferential Attachment (Green) with 50% Bait and 50% Edge Coverage against the CORE Yeast PPI Network (Red)

Mentions: A comparison of the core yeast PPI network against the resulting network is given in Figure 6. As can be seen, the topological features of both the full yeast PPI network and the core yeast PPI can still be closely captured by the networks obtained via the duplication model, which have been subject to sampling errors.


Not all scale-free networks are born equal: the role of the seed graph in PPI network evolution.

Hormozdiari F, Berenbrink P, Przulj N, Sahinalp SC - PLoS Comput. Biol. (2007)

Comparison of Duplication (Blue) and Preferential Attachment (Green) with 50% Bait and 50% Edge Coverage against the CORE Yeast PPI Network (Red)
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC1913096&req=5

pcbi-0030118-g006: Comparison of Duplication (Blue) and Preferential Attachment (Green) with 50% Bait and 50% Edge Coverage against the CORE Yeast PPI Network (Red)
Mentions: A comparison of the core yeast PPI network against the resulting network is given in Figure 6. As can be seen, the topological features of both the full yeast PPI network and the core yeast PPI can still be closely captured by the networks obtained via the duplication model, which have been subject to sampling errors.

Bottom Line: The (asymptotic) degree distributions of the best-known "scale-free" network models are all similar and are independent of the seed graph used; hence, it has been tempting to assume that networks generated by these models are generally similar.In this paper, we observe that several key topological features of such networks depend heavily on the specific model and the seed graph used.Furthermore, we show that starting with the "right" seed graph (typically a dense subgraph of the protein-protein interaction network analyzed), the duplication model captures many topological features of publicly available protein-protein interaction networks very well.

View Article: PubMed Central - PubMed

Affiliation: School of Computing Science, Simon Fraser University, Burnaby, British Columbia, Canada.

ABSTRACT
The (asymptotic) degree distributions of the best-known "scale-free" network models are all similar and are independent of the seed graph used; hence, it has been tempting to assume that networks generated by these models are generally similar. In this paper, we observe that several key topological features of such networks depend heavily on the specific model and the seed graph used. Furthermore, we show that starting with the "right" seed graph (typically a dense subgraph of the protein-protein interaction network analyzed), the duplication model captures many topological features of publicly available protein-protein interaction networks very well.

Show MeSH