Coarse-graining and self-dissimilarity of complex networks

Shalev Itzkovitz*, Reuven Levitt, Nadav Kashtan, Ron Milo, Michael Itzkovitz, Uri Alon

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

103 Scopus citations

Abstract

Can complex engineered and biological networks be coarse-grained into smaller and more understandable versions in which each node represents an entire pattern in the original network? To address this, we define coarse-graining units as connectivity patterns which can serve as the nodes of a coarse-grained network and present algorithms to detect them. We use this approach to systematically reverse-engineer electronic circuits, forming understandable high-level maps from incomprehensible transistor wiring: first, a coarse-grained version in which each node is a gate made of several transistors is established. Then the coarse-grained network is itself coarse-grained, resulting in a high-level blueprint in which each node is a circuit module made of many gates. We apply our approach also to a mammalian protein signal-transduction network, to find a simplified coarse-grained network with three main signaling channels that resemble multi-layered perceptrons made of cross-interacting MAP-kinase cascades. We find that both biological and electronic networks are "self-dissimilar," with different network motifs at each level. The present approach may be used to simplify a variety of directed and nondirected, natural and designed networks.

Original languageAmerican English
Article number016127
JournalPhysical Review E
Volume71
Issue number1
DOIs
StatePublished - Jan 2005
Externally publishedYes

Fingerprint

Dive into the research topics of 'Coarse-graining and self-dissimilarity of complex networks'. Together they form a unique fingerprint.

Cite this