The Institute of Scientific Information for Social Sciences RAS, 51/21 Nakhimov Avenue, Moscow, 117997, Russia; Sobolev Institute of Mathematics SB RAS, 13 Pevtsov Str., Omsk, 644099, Russia.
The Institute of Scientific Information for Social Sciences RAS, 51/21 Nakhimov Avenue, Moscow, 117997, Russia; The I. M. Sechenov Institute of Evolutionary Physiology and Biochemistry RAS, pr. Torez 44, Saint-Petersburg, 194223, Russia.
Biosystems. 2021 Feb;200:104312. doi: 10.1016/j.biosystems.2020.104312. Epub 2020 Dec 2.
The field of evolutionary algorithms (EAs) emerged in the area of computer science due to transfer of ideas from biology and developed independently for several decades, enriched with techniques from probability theory, complexity theory and optimization methods. In this paper, we consider some recent results form the EAs theory transferred back into biology. The well-known biotechnological procedure SELEX (Systematic Evolution of Ligands by EXponential enrichment) is viewed as an experimental implementation of an evolutionary algorithm. Theoretical bounds on EAs runtime are applied to model SELEX search for a regulatory region consisting of promoter and enhancer sequences. A comparison of theoretical bounds to the results of computational simulation indicates some cases where the theoretical bounds give favorable prediction, while simulation requires prohibitive computational resource.
进化算法（EAs）领域源于计算机科学领域中生物学思想的转移，并独立发展了几十年，其技术丰富了概率论、复杂性理论和优化方法。在本文中，我们考虑了一些从进化算法理论中转移回生物学的最新成果。众所周知的生物技术程序 SELEX（通过指数富集的配体系统进化）被视为进化算法的实验实现。我们将进化算法的运行时间的理论界应用于由启动子和增强子序列组成的调控区的 SELEX 搜索模型。将理论界与计算模拟的结果进行比较表明，在某些情况下，理论界可以给出有利的预测，而模拟则需要大量的计算资源。
