Computationally efficient measure of topological redundancy of biological and social networks

Réka Albert, Bhaskar DasGupta, Rashmi Hegde, Gowri Sangeetha Sivanathan, Anthony Gitter, Gamze Gürsoy, Pradyut Paul, and Eduardo Sontag
Phys. Rev. E 84, 036117 – Published 29 September 2011

Abstract

It is well known that biological and social interaction networks have a varying degree of redundancy, though a consensus of the precise cause of this is so far lacking. In this paper, we introduce a topological redundancy measure for labeled directed networks that is formal, computationally efficient, and applicable to a variety of directed networks such as cellular signaling, and metabolic and social interaction networks. We demonstrate the computational efficiency of our measure by computing its value and statistical significance on a number of biological and social networks with up to several thousands of nodes and edges. Our results suggest a number of interesting observations: (1) Social networks are more redundant that their biological counterparts, (2) transcriptional networks are less redundant than signaling networks, (3) the topological redundancy of the C. elegans metabolic network is largely due to its inclusion of currency metabolites, and (4) the redundancy of signaling networks is highly (negatively) correlated with the monotonicity of their dynamics.

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  • Received 19 March 2011

DOI:https://doi.org/10.1103/PhysRevE.84.036117

©2011 American Physical Society

Authors & Affiliations

Réka Albert*

  • Department of Physics, Pennsylvania State University, University Park, Pennsylvania 16802, USA

Bhaskar DasGupta, Rashmi Hegde, and Gowri Sangeetha Sivanathan§

  • Department of Computer Science, University of Illinois at Chicago, Chicago, Illinois 60607, USA

Anthony Gitter

  • Computer Science Department, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213, USA

Gamze Gürsoy

  • Department of Bioengineering, University of Illinois at Chicago, Chicago, Illinois 60607, USA

Pradyut Paul**

  • Junior, Neuqua Valley High School, Naperville, Illinois 60564, USA

Eduardo Sontag††

  • Department of Mathematics, Rutgers University, New Brunswick, New Jersey 08903, USA

  • *ralbert@phys.psu.edu; www.phys.psu.edu/ ˜ralbert
  • dasgupta@cs.uic.edu; www.cs.uic.edu/ ˜dasgupta; Author to whom correspondence should be sent.
  • rashmihegde.g@gmail.com
  • §gsivan2@uic.edu
  • agitter@cs.cmu.edu; www.cs.cmu.edu/ ˜agitter
  • gamze.gursoy@gmail.com; www2.uic.edu/ ˜ggurso2
  • **paulpradyut@yahoo.com
  • ††sontag@math.rutgers.edu; www.math.rutgers.edu/ sontag

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Vol. 84, Iss. 3 — September 2011

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