High-throughput mathematical analysis identifies Turing networks for patterning with equally diffusing signals
High-throughput mathematical analysis identifies Turing networks for patterning with equally diffusing signals
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2016
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eLife ; 5 (2016). - e14022. - eLife Sciences Publications. - eISSN 2050-084X
Zusammenfassung
The Turing reaction-diffusion model explains how identical cells can self-organize to form spatial patterns. It has been suggested that extracellular signaling molecules with different diffusion coefficients underlie this model, but the contribution of cell-autonomous signaling components is largely unknown. We developed an automated mathematical analysis to derive a catalog of realistic Turing networks. This analysis reveals that in the presence of cell-autonomous factors, networks can form a pattern with equally diffusing signals and even for any combination of diffusion coefficients. We provide a software (available at http://www.RDNets.com) to explore these networks and to constrain topologies with qualitative and quantitative experimental data. We use the software to examine the self-organizing networks that control embryonic axis specification and digit patterning. Finally, we demonstrate how existing synthetic circuits can be extended with additional feedbacks to form Turing reaction-diffusion systems. Our study offers a new theoretical framework to understand multicellular pattern formation and enables the wide-spread use of mathematical biology to engineer synthetic patterning systems.
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570 Biowissenschaften, Biologie
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MARCON, Luciano, Xavier DIEGO, James SHARPE, Patrick MÜLLER, 2016. High-throughput mathematical analysis identifies Turing networks for patterning with equally diffusing signals. In: eLife. eLife Sciences Publications. 5, e14022. eISSN 2050-084X. Available under: doi: 10.7554/eLife.14022BibTex
@article{Marcon2016Hight-55590, year={2016}, doi={10.7554/eLife.14022}, title={High-throughput mathematical analysis identifies Turing networks for patterning with equally diffusing signals}, volume={5}, journal={eLife}, author={Marcon, Luciano and Diego, Xavier and Sharpe, James and Müller, Patrick}, note={Article Number: e14022} }
RDF
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