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Robustness and Information Propagation in Attractors of Random Boolean Networks

Overview of attention for article published in PLOS ONE, July 2012
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Title
Robustness and Information Propagation in Attractors of Random Boolean Networks
Published in
PLOS ONE, July 2012
DOI 10.1371/journal.pone.0042018
Pubmed ID
Authors

Jason Lloyd-Price, Abhishekh Gupta, Andre S. Ribeiro

Abstract

Attractors represent the long-term behaviors of Random Boolean Networks. We study how the amount of information propagated between the nodes when on an attractor, as quantified by the average pairwise mutual information (I(A)), relates to the robustness of the attractor to perturbations (R(A)). We find that the dynamical regime of the network affects the relationship between I(A) and R(A). In the ordered and chaotic regimes, I(A) is anti-correlated with R(A), implying that attractors that are highly robust to perturbations have necessarily limited information propagation. Between order and chaos (for so-called "critical" networks) these quantities are uncorrelated. Finite size effects cause this behavior to be visible for a range of networks, from having a sensitivity of 1 to the point where I(A) is maximized. In this region, the two quantities are weakly correlated and attractors can be almost arbitrarily robust to perturbations without restricting the propagation of information in the network.

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Geographical breakdown

Country Count As %
Mexico 1 4%
United States 1 4%
Italy 1 4%
Unknown 24 89%

Demographic breakdown

Readers by professional status Count As %
Student > Master 6 22%
Student > Bachelor 4 15%
Professor 4 15%
Researcher 4 15%
Student > Ph. D. Student 4 15%
Other 3 11%
Unknown 2 7%
Readers by discipline Count As %
Physics and Astronomy 7 26%
Agricultural and Biological Sciences 6 22%
Mathematics 2 7%
Biochemistry, Genetics and Molecular Biology 2 7%
Computer Science 2 7%
Other 4 15%
Unknown 4 15%