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用于定向进化的进化算法与合成生物学：对彼得·A·惠格姆、格兰特·迪克和詹姆斯·麦克劳林所著《论进化算法中基因型到表型的映射》的评论

Evolutionary algorithms and synthetic biology for directed evolution: commentary on "on the mapping of genotype to phenotype in evolutionary algorithms" by Peter A. Whigham, Grant Dick, and James Maclaurin.

作者信息

Kell Douglas B

机构信息

School of Chemistry, The University of Manchester, 131, Princess St, Manchester, Lancs, M1 7DN UK.

The Manchester Institute of Biotechnology, The University of Manchester, 131, Princess St, Manchester, Lancs, M1 7DN UK.

出版信息

Genet Program Evolvable Mach. 2017;18(3):373-378. doi: 10.1007/s10710-017-9292-1. Epub 2017 Mar 29.

DOI:10.1007/s10710-017-9292-1
PMID:29033669
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5618731/
Abstract

I rehearse two issues around the commentary of Whigham and colleagues. (1) There really are many more reasons than those given as to why natural evolution cannot reasonably find or select the 'optimal' individual. (2) A series of experimental molecular biology programmes, known generically as directed evolution, can use operators and selection schemes that natural evolution cannot. When developed further using the methods of synthetic biology, there are no operators or schemes for in silico evolution that cannot be applied precisely to directed evolution. The issues raised apply only to natural evolution but not to directed evolution.

摘要

我围绕惠格姆及其同事的评论阐述两个问题。（1）实际上，自然进化无法合理地找到或选择“最优”个体的原因远不止所给出的那些。（2）一系列统称为定向进化的实验性分子生物学程序，可以使用自然进化所不能使用的操作子和选择方案。当使用合成生物学方法进一步发展时，计算机进化中不存在不能精确应用于定向进化的操作子或方案。所提出的这些问题仅适用于自然进化，而不适用于定向进化。

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