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Software Helps Decrypt Embryonic Development

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A self-organizing labyrinthine Turing pattern.

A model of a classical Turing network compared to the extended Turing networks analyzed with the software RDNets.

Credit: Mller/MPI f. Developmental Biology

Researchers from the Max Planck Society's Friedrich Miescher Laboratory have devised mathematical strategies and software for the systematic analysis of realistic pattern-forming networks involving more than two molecules.

Famed mathematician Alan Turing mathematically demonstrated more than 60 years ago that two signaling molecules can form spatial patterns in an embryo if one molecule moves faster than the other. The subsequent high and low molecule concentrations provide the cells with information on how to differentiate and where to form different body parts.

The Miescher Lab researchers' RDNets software analyzes and models pattern formation in reaction-diffusion networks with both mobile and immobile molecules. RDNets screened millions of possible reaction-diffusion networks to find most of the newly identified patterning networks do not have to meet a condition of differential signal mobility. Instead, patterns also can form when the signaling molecules are equally mobile or even with any mix of signal mobilities.

The software analyzed several developmental systems, and the scientists learned RDNets could find use in bioengineering because it enables users to simulate many patterning processes and design underlying gene regulatory circuits that can be constructed synthetically.

From Max Planck Gessellschaft
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Abstracts Copyright © 2016 Information Inc., Bethesda, Maryland, USA


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