The algorithmic beauty of sea shells
The algorithmic beauty of sea shells
Theoretical Computer Science - Special issue: Computational systems biology
On the Computational Power of Biochemistry
AB '08 Proceedings of the 3rd international conference on Algebraic Biology
Scalable simulation of cellular signaling networks
APLAS'07 Proceedings of the 5th Asian conference on Programming languages and systems
Biochemical reaction rules with constraints
ESOP'11/ETAPS'11 Proceedings of the 20th European conference on Programming languages and systems: part of the joint European conferences on theory and practice of software
The biochemical abstract machine BIOCHAM
CMSB'04 Proceedings of the 20 international conference on Computational Methods in Systems Biology
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For decades, scientists have sought to elucidate self-organized patterning during development of higher organisms. It has been shown that cell interaction plays a key role in this process. One example is the community effect, an interaction among undifferentiated cells. The community effect allows cell population to forge a common identity, that is, coordinated and sustained tissue-specific gene expression. The community effect was originally observed in muscle differentiation in Xenopus embryos, and is now thought to be a widespread phenomenon. From a modelling point of view, the community effect is the existence of a threshold size of cell populations, above which the probability of tissue-specific gene expression for a sustained period increases significantly. Below this threshold size, the cell population fails to maintain tissue-specific gene expression after the initial induction. In this work, we examine the dynamics of a community effect in space and investigate its roles in two other processes of self-organized patterning by diffusible factors: Turing's reaction-diffusion system and embryonic induction by morphogens. Our major results are the following. First, we show that, starting from a one-dimensional space model with the simplest possible feedback loop, a community effect spreads in an unlimited manner in space. Second, this unrestricted expansion of a community effect can be avoided by additional negative feedback. In Turing's reaction-diffusion system with a built-in community effect, if induction is localized, sustained activation also remains localized. Third, when a simple cross-repression gene circuitry is combined with a community effect loop, the system self-organizes. A gene expression pattern with a well-demarcated boundary appears in response to a transient morphogen gradient. Surprisingly, even when the morphogen distribution eventually becomes uniform, the system can maintain the pattern. The regulatory network thus confers memory of morphogen dynamics.