In this work, we explicitly consider the evolution of the Standard Genetic Code (SGC) by assuming two evolutionary stages, to wit, the primeval RNY code and two intermediate codes in between. We used network theory and graph theory to measure the connectivity of each phenotypic graph. The connectivity values are compared to the values of the codes under different randomization scenarios. An error-correcting optimal code is one in which the algebraic connectivity is minimized. We show that the SGC is optimal in regard to its robustness and error-tolerance when compared to all random codes under different assumptions.

中文翻译：

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表型图和进化展开为最佳的标准遗传密码。

在这项工作中，我们通过假设两个进化阶段，即原始RNY码和介于两者之间的两个中间码，来明确考虑标准遗传密码（SGC）的进化。我们使用网络理论和图论来测量每个表型图的连通性。将连接性值与不同随机情况下的代码值进行比较。纠错最佳代码是其中代数连接性最小的代码。我们显示，与不同假设下的所有随机代码相比，SGC在鲁棒性和容错性方面是最佳的。