by Schneider CM, de Arcangelis L, Herrmann HJ
Abstract:
A major issue in biology is the understanding of the interactions between proteins. These interactions can be described by a network, where the proteins are modeled by nodes and the interactions by edges. The origin of these protein networks is not well understood yet. Here we present a two-step model, which generates clusters with the same topological properties as networks for protein-protein interactions, namely, the same degree distribution, cluster size distribution, clustering coefficient, and shortest path length. The biological and model networks are not scale-free but exhibit small-world features. The model allows the fitting of different biological systems by tuning a single parameter.
Reference:
Modeling the topology of protein interaction networks (Schneider CM, de Arcangelis L, Herrmann HJ), In PHYSICAL REVIEW E, STATISTICAL, NONLINEAR, AND SOFT MATTER PHYSICS, 2011. (Articolo in rivista)
Bibtex Entry:
@article{cri11,
author = {Schneider CM, and de Arcangelis L, and Herrmann HJ,},
title = {Modeling the topology of protein interaction networks},
note = {Articolo in rivista},
issn = {1539-3755},
journal = {PHYSICAL REVIEW E, STATISTICAL, NONLINEAR, AND SOFT MATTER PHYSICS},
doi = {10.1103/PhysRevE.84.016112},
year = {2011},
wosId = {000293454200002},
scopusId = {2-s2.0-79961112818},
abstract = {A major issue in biology is the understanding of the interactions between proteins. These interactions can be described by a network, where the proteins are modeled by nodes and the interactions by edges. The origin of these protein networks is not well understood yet. Here we present a two-step model, which generates clusters with the same topological properties as networks for protein-protein interactions, namely, the same degree distribution, cluster size distribution, clustering coefficient, and shortest path length. The biological and model networks are not scale-free but exhibit small-world features. The model allows the fitting of different biological systems by tuning a single parameter.}
}