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BoolSi: A Tool for Distributed Simulations and Analysis of Boolean Networks Cover

BoolSi: A Tool for Distributed Simulations and Analysis of Boolean Networks

Open Access
|Oct 2020

Figures & Tables

jors-8-308-g1.png
Figure 1

BoolSi output showing an attractor of a 30-node network (model of cambium regulation from [14], used in Section Case study). The activity coefficient of the node CK associated with each of roughly 0.0115 · 230 ≈ 12,348,031 network states sk leading to this attractor is αkCK=56.

jors-8-308-g2.png
Figure 2

Cambium regulation network from [14]. Bigger, green-colored nodes represent hormonal signals produced outside cambium; their states do not change throughout each simulation run. Dashed and solid lines represent activation and inhibition respectively.

jors-8-308-g3.png
Figure 3

BoolSi output showing the results of attractor analysis. Cell in i-th row and j-th column shows ρij, Spearman’s correlation coefficient between activity of the nodes i and j in the attractors. In the lower-right triangle, the values corresponding to p-values ≥ 0.05 are hidden.

DOI: https://doi.org/10.5334/jors.308 | Journal eISSN: 2049-9647
Language: English
Submitted on: Oct 27, 2019
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Accepted on: Sep 17, 2020
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Published on: Oct 7, 2020
Published by: Ubiquity Press
In partnership with: Paradigm Publishing Services
Publication frequency: 1 issue per year

© 2020 Vladyslav Oles, Anton Kukushkin, published by Ubiquity Press
This work is licensed under the Creative Commons Attribution 4.0 License.