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肢体中的自组织:手指发育的图灵机制。

Self-organization in the limb: a Turing mechanism for digit development.

作者信息

Cooper Kimberly L

机构信息

University of California San Diego, 9500 Gilman Drive, La Jolla, CA 92093-0380, USA.

出版信息

Curr Opin Genet Dev. 2015 Jun;32:92-7. doi: 10.1016/j.gde.2015.02.001. Epub 2015 Mar 26.

Abstract

The statistician George E. P. Box stated, 'Essentially all models are wrong, but some are useful.' (Box GEP, Draper NR: Empirical Model-Building and Response Surfaces. Wiley; 1987). Modeling biological processes is challenging for many of the reasons classically trained developmental biologists often resist the idea that black and white equations can explain the grayscale subtleties of living things. Although a simplified mathematical model of development will undoubtedly fall short of precision, a good model is exceedingly useful if it raises at least as many testable questions as it answers. Self-organizing Turing models that simulate the pattern of digits in the hand replicate events that have not yet been explained by classical approaches. The union of theory and experimentation has recently identified and validated the minimal components of a Turing network for digit pattern and triggered a cascade of questions that will undoubtedly be well-served by the continued merging of disciplines.

摘要

统计学家乔治·E·P·博克斯指出:“实际上,所有模型都是错误的,但有些是有用的。”(博克斯GEP、德雷珀NR:《经验模型构建与响应曲面》。威利出版社;1987年)。对许多经典训练的发育生物学家来说,构建生物过程模型具有挑战性,原因在于他们常常抵制黑白分明的方程式能够解释生物灰度细微差别的观点。尽管简化的发育数学模型无疑在精确性上有所欠缺,但如果一个好的模型所提出的可测试问题至少与它所回答的问题一样多,那么它就极其有用。模拟手部数字模式的自组织图灵模型复制了经典方法尚未解释的事件。理论与实验的结合最近已经识别并验证了用于数字模式的图灵网络的最小组成部分,并引发了一系列问题,而学科的持续融合无疑将很好地解决这些问题。

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