Not all scale-free networks are born equal: the role of the seed graph in PPI network evolution.
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.
Hormozdiari
Fereydoun
F
School of Computing Science, Simon Fraser University, Burnaby, British Columbia, Canada.
Berenbrink
Petra
P
Przulj
Natasa
N
Sahinalp
S Cenk
SC
D016000:Cluster Analysis; D003198:Computer Simulation; D030562:Databases, Protein; D019143:Evolution, Molecular; D020440:Gene Duplication; D053263:Gene Regulatory Networks / Q000502:physiology*; D016571:Neural Networks, Computer; D025941:Protein Interaction Mapping / Q000379:methods*; D020543:Proteome / Q000235:genetics / Q000378:metabolism; D012015:Reference Standards; D012441:Saccharomyces cerevisiae / Q000235:genetics / Q000378:metabolism; D029701:Saccharomyces cerevisiae Proteins / Q000378:metabolism; D015398:Signal Transduction; D049490:Systems Biology / Q000379:methods; D013598:Systems Theory
D020543:Proteome; D029701:Saccharomyces cerevisiae Proteins