An effective network reduction approach to find the dynamical repertoire of discrete dynamic networks

Jorge G.T. Zañudo, Reka Z. Albert

Research output: Contribution to journalArticle

47 Citations (Scopus)

Abstract

Discrete dynamic models are a powerful tool for the understanding and modeling of large biological networks. Although a lot of progress has been made in developing analysis tools for these models, there is still a need to find approaches that can directly relate the network structure to its dynamics. Of special interest is identifying the stable patterns of activity, i.e., the attractors of the system. This is a problem for large networks, because the state space of the system increases exponentially with network size. In this work, we present a novel network reduction approach that is based on finding network motifs that stabilize in a fixed state. Notably, we use a topological criterion to identify these motifs. Specifically, we find certain types of strongly connected components in a suitably expanded representation of the network. To test our method, we apply it to a dynamic network model for a type of cytotoxic T cell cancer and to an ensemble of random Boolean networks of size up to 200. Our results show that our method goes beyond reducing the network and in most cases can actually predict the dynamical repertoire of the nodes (fixed states or oscillations) in the attractors of the system.

Original languageEnglish (US)
Article number025111
JournalChaos
Volume23
Issue number2
DOIs
StatePublished - Jan 1 2013

Fingerprint

Discrete Dynamics
Dynamic Networks
T-cells
Dynamic models
Attractor
Dynamic Model
Random Boolean Networks
Biological Networks
Discrete Model
Connected Components
Network Structure
Network Model
Cancer
State Space
Ensemble
Oscillation
Predict
dynamic models
Vertex of a graph
Modeling

All Science Journal Classification (ASJC) codes

  • Statistical and Nonlinear Physics
  • Mathematical Physics
  • Physics and Astronomy(all)
  • Applied Mathematics

Cite this

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An effective network reduction approach to find the dynamical repertoire of discrete dynamic networks. / Zañudo, Jorge G.T.; Albert, Reka Z.

In: Chaos, Vol. 23, No. 2, 025111, 01.01.2013.

Research output: Contribution to journalArticle

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