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图灵的生物模式形成模型与鲁棒性问题。

Turing's model for biological pattern formation and the robustness problem.

机构信息

Centre for Mathematical Biology, Mathematical Institute, University of Oxford, 24-29 St Giles', Oxford OX1 3PN, UK ; Oxford Centre for Integrative Systems Biology, Department of Biochemistry, University of Oxford, South Parks Road OX1 3QU, UK.

出版信息

Interface Focus. 2012 Aug 6;2(4):487-96. doi: 10.1098/rsfs.2011.0113. Epub 2012 Feb 8.

Abstract

One of the fundamental questions in developmental biology is how the vast range of pattern and structure we observe in nature emerges from an almost uniformly homogeneous fertilized egg. In particular, the mechanisms by which biological systems maintain robustness, despite being subject to numerous sources of noise, are shrouded in mystery. Postulating plausible theoretical models of biological heterogeneity is not only difficult, but it is also further complicated by the problem of generating robustness, i.e. once we can generate a pattern, how do we ensure that this pattern is consistently reproducible in the face of perturbations to the domain, reaction time scale, boundary conditions and so forth. In this paper, not only do we review the basic properties of Turing's theory, we highlight the successes and pitfalls of using it as a model for biological systems, and discuss emerging developments in the area.

摘要

发育生物学的基本问题之一是,我们在自然界中观察到的广泛的形态和结构是如何从几乎均匀同质的受精卵中产生的。特别是,尽管生物系统受到众多噪声源的影响,但它们维持鲁棒性的机制仍然是个谜。假设生物异质性的合理理论模型不仅困难,而且由于生成鲁棒性的问题而变得更加复杂,即一旦我们可以生成一个模式,我们如何确保在面对对域、反应时间尺度、边界条件等的干扰时,这个模式是始终可重复的。在本文中,我们不仅回顾了图灵理论的基本性质,还强调了将其用作生物系统模型的成功和陷阱,并讨论了该领域的新发展。

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本文引用的文献

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Influence of stochastic domain growth on pattern nucleation for diffusive systems with internal noise.随机域生长对具有内部噪声的扩散系统模式成核的影响。
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Stochastic Turing patterns in the Brusselator model.布鲁塞尔振子模型中的随机图灵模式。
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