150 Years since the birth of Lev Berg: Nomogenesis is more relevant today than ever

IF 2.1 4区 生物学 Q2 BIOLOGY
Biosystems Pub Date : 2026-01-01 Epub Date: 2025-12-04 DOI:10.1016/j.biosystems.2025.105670
A.V. Melkikh
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引用次数: 0

Abstract

This article is dedicated to the 150th anniversary of the evolutionist Lev Berg and explores his evolutionary ideas. Concepts such as convergence, parallelism, and mimicry are examined. A substantial body of modern research supports Berg's view of evolution as a directional process. In particular, Berg's conclusion that such complex living structures could not have arisen by chance is fully supported by modern calculations. Contemporary examples of parallelism research among animals (including domesticated ones) are considered. Contemporary examples of mimicry research are also considered. The extensive parallelism of species, organs, tissues, etc., also strongly supports Berg's theory. One of Berg's most important ideas was the improbability of random evolution in living systems. The lack of a solution to this problem is one of the main shortcomings of Darwinism. Modern genomic research allows us to further tighten the requirements for this probability, making it negligible.
列夫·伯格诞辰150周年:生理发育在今天比以往任何时候都更有意义。
这篇文章是为了纪念进化论者列夫·伯格诞辰150周年,并探讨他的进化思想。概念,如收敛,平行和模仿进行了检查。大量现代研究支持伯格的观点,即进化是一个有方向的过程。特别是,伯格关于这种复杂的生命结构不可能偶然出现的结论,完全得到了现代计算的支持。考虑了当代动物(包括驯化动物)之间平行研究的例子。还考虑了当代模仿研究的例子。物种、器官、组织等的广泛相似性也有力地支持了伯格的理论。伯格最重要的思想之一是生命系统中随机进化的不可能性。缺乏解决这个问题的方法是达尔文主义的主要缺点之一。现代基因组研究使我们能够进一步收紧对这种概率的要求,使其可以忽略不计。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Biosystems
Biosystems 生物-生物学
CiteScore
3.70
自引率
18.80%
发文量
129
审稿时长
34 days
期刊介绍: BioSystems encourages experimental, computational, and theoretical articles that link biology, evolutionary thinking, and the information processing sciences. The link areas form a circle that encompasses the fundamental nature of biological information processing, computational modeling of complex biological systems, evolutionary models of computation, the application of biological principles to the design of novel computing systems, and the use of biomolecular materials to synthesize artificial systems that capture essential principles of natural biological information processing.
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