Literature DB >> 19932703

Cooperative differentiation through clustering in multicellular populations.

A Koseska1, E Ullner, E Volkov, J Kurths, J García-Ojalvo.   

Abstract

The coordinated development of multicellular organisms is driven by intercellular communication. Differentiation into diverse cell types is usually associated with the existence of distinct attractors of gene regulatory networks, but how these attractors emerge from cell-cell coupling is still an open question. In order to understand and characterize the mechanisms through which coexisting attractors arise in multicellular systems, here we systematically investigate the dynamical behavior of a population of synthetic genetic oscillators coupled by chemical means. Using bifurcation analysis and numerical simulations, we identify various attractors and attempt to deduce from these findings a way to predict the organized collective behavior of growing populations. Our results show that dynamical clustering is a generic property of multicellular systems. We argue that such clustering might provide a basis for functional differentiation and variability in biological systems. Copyright 2009 Elsevier Ltd. All rights reserved.

Mesh:

Year:  2009        PMID: 19932703     DOI: 10.1016/j.jtbi.2009.11.007

Source DB:  PubMed          Journal:  J Theor Biol        ISSN: 0022-5193            Impact factor:   2.691


  12 in total

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5.  Analysing dynamical behavior of cellular networks via stochastic bifurcations.

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7.  A comparison of Monte Carlo-based Bayesian parameter estimation methods for stochastic models of genetic networks.

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8.  Basin stability measure of different steady states in coupled oscillators.

Authors:  Sarbendu Rakshit; Bidesh K Bera; Soumen Majhi; Chittaranjan Hens; Dibakar Ghosh
Journal:  Sci Rep       Date:  2017-04-05       Impact factor: 4.379

9.  Pluripotency, Differentiation, and Reprogramming: A Gene Expression Dynamics Model with Epigenetic Feedback Regulation.

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10.  Parameter estimation methods for chaotic intercellular networks.

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Journal:  PLoS One       Date:  2013-11-25       Impact factor: 3.240

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