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BMC Bioinformatics. 2016 Dec 22;17(Suppl 19):506. doi: 10.1186/s12859-016-1363-4.

Statistical ensemble of gene regulatory networks of macrophage differentiation.

Author information

1
Institute for Applied Computing, National Research Council of Italy, Via dei Taurini 19, Rome, 00185, Italy. f.castiglione@iac.cnr.it.
2
Institute for Applied Computing, National Research Council of Italy, Via dei Taurini 19, Rome, 00185, Italy.
3
Department of Biology, University of Tor Vergata, Via della ricerca scientifica 1, Rome, 00133, Italy.
4
Department of Mathematics and Statistics, American University of Sharjah, P.O.Box 26666, Sharjah, UAE.

Abstract

BACKGROUND:

Macrophages cover a major role in the immune system, being the most plastic cell yielding several key immune functions.

METHODS:

Here we derived a minimalistic gene regulatory network model for the differentiation of macrophages into the two phenotypes M1 (pro-) and M2 (anti-inflammatory).

RESULTS:

To test the model, we simulated a large number of such networks as in a statistical ensemble. In other words, to enable the inter-cellular crosstalk required to obtain an immune activation in which the macrophage plays its role, the simulated networks are not taken in isolation but combined with other cellular agents, thus setting up a discrete minimalistic model of the immune system at the microscopic/intracellular (i.e., genetic regulation) and mesoscopic/intercellular scale.

CONCLUSIONS:

We show that within the mesoscopic level description of cellular interaction and cooperation, the gene regulatory logic is coherent and contributes to the overall dynamics of the ensembles that shows, statistically, the expected behaviour.

KEYWORDS:

Agent-based modelling; Gene regulatory network; Macrophage differentiation; Multiscale modelling

PMID:
28155642
PMCID:
PMC5260144
DOI:
10.1186/s12859-016-1363-4
[Indexed for MEDLINE]
Free PMC Article

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