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对称性和简单性自发地从进化的算法本质中出现。

Symmetry and simplicity spontaneously emerge from the algorithmic nature of evolution.

机构信息

Department of Mathematics, University of Bergen, Bergen 5007, Norway.

Computational Biology Unit, University of Bergen, Bergen 5008, Norway.

出版信息

Proc Natl Acad Sci U S A. 2022 Mar 15;119(11):e2113883119. doi: 10.1073/pnas.2113883119. Epub 2022 Mar 11.

Abstract

SignificanceWhy does evolution favor symmetric structures when they only represent a minute subset of all possible forms? Just as monkeys randomly typing into a computer language will preferentially produce outputs that can be generated by shorter algorithms, so the coding theorem from algorithmic information theory predicts that random mutations, when decoded by the process of development, preferentially produce phenotypes with shorter algorithmic descriptions. Since symmetric structures need less information to encode, they are much more likely to appear as potential variation. Combined with an arrival-of-the-frequent mechanism, this algorithmic bias predicts a much higher prevalence of low-complexity (high-symmetry) phenotypes than follows from natural selection alone and also explains patterns observed in protein complexes, RNA secondary structures, and a gene regulatory network.

摘要

意义为什么进化会青睐对称结构,而它们只代表所有可能形式的一小部分?就像猴子在随机输入计算机语言时,会优先产生更短算法生成的输出一样,因此算法信息论的编码定理预测,随机突变在通过发育过程解码时,会优先产生具有更短算法描述的表型。由于对称结构需要较少的信息来编码,因此它们更有可能作为潜在的变异出现。结合频繁出现的机制,这种算法偏差预测了比仅由自然选择所导致的更高的低复杂度(高对称性)表型的出现率,并且还解释了在蛋白质复合物、RNA 二级结构和基因调控网络中观察到的模式。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cdbd/8931234/795c1d7799d0/pnas.2113883119fig01.jpg

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