Inferring network mechanisms: the Drosophila melanogaster protein interaction network. Academic Article uri icon

Overview

abstract

  • Naturally occurring networks exhibit quantitative features revealing underlying growth mechanisms. Numerous network mechanisms have recently been proposed to reproduce specific properties such as degree distributions or clustering coefficients. We present a method for inferring the mechanism most accurately capturing a given network topology, exploiting discriminative tools from machine learning. The Drosophila melanogaster protein network is confidently and robustly (to noise and training data subsampling) classified as a duplication-mutation-complementation network over preferential attachment, small-world, and a duplication-mutation mechanism without complementation. Systematic classification, rather than statistical study of specific properties, provides a discriminative approach to understand the design of complex networks.

publication date

  • February 22, 2005

Research

keywords

  • Drosophila Proteins

Identity

PubMed Central ID

  • PMC552930

Scopus Document Identifier

  • 14744273317

Digital Object Identifier (DOI)

  • 10.1073/pnas.0409515102

PubMed ID

  • 15728374

Additional Document Info

volume

  • 102

issue

  • 9