Random sampling versus exact enumeration of attractors in random boolean networks

6Citations
Citations of this article
27Readers
Mendeley users who have this article in their library.

Abstract

We clarify the effect different sampling methods and weighting schemes have on the statistics of attractors in ensembles of random Boolean networks (RBNs). We directly measure the cycle lengths of attractors and the sizes of basins of attraction in RBNs using exact enumeration of the state space. In general, the distribution of attractor lengths differs markedly from that obtained by randomly choosing an initial state and following the dynamics to reach an attractor. Our results indicate that the former distribution decays as a power law with exponent 1 for all connectivities K > 1 in the infinite system size limit. In contrast, the latter distribution decays as a power law only for K = 2. This is because the mean basin size grows linearly with the attractor cycle length for K > 2, and is statistically independent of the cycle length for K = 2. We also find that the histograms of basin sizes are strongly peaked at integer multiples of powers of two for K < 3. © IOP Publishing Ltd and Deutsche Physikalische Gesellschaft.

Cite

CITATION STYLE

APA

Berdahl, A., Shreim, A., Sood, V., Paczuski, M., & Davidsen, J. (2009). Random sampling versus exact enumeration of attractors in random boolean networks. New Journal of Physics, 11. https://doi.org/10.1088/1367-2630/11/4/043024

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free