分子进化原理:多层次学习理论的非平衡热力学概念》。

IF 2.1 3区 生物学 Q4 BIOCHEMISTRY & MOLECULAR BIOLOGY
Jens Smiatek
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引用次数: 0

摘要

我们提出了一种研究分子进化的多级学习理论的非平衡热力学方法。通过这种方法,我们可以研究分子进化过程的明确时间依赖性及其对熵产生的影响。通过解读数学表达式,我们可以发现影响分子进化过程熵产生的两个主要因素是突变和基因转移效应。因此,我们的研究结果表明,在进化过程中,生物对外部条件的最佳适应是由最小熵产生原则驱动的。这些结果也可以解释为以前一些学习理论假设的基础。尽管我们的宏观方法需要一定的简化,但它允许我们参照众所周知的生物过程,用热力学描述来解释分子进化过程。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Principles of Molecular Evolution: Concepts from Non-equilibrium Thermodynamics for the Multilevel Theory of Learning.

We present a non-equilibrium thermodynamics approach to the multilevel theory of learning for the study of molecular evolution. This approach allows us to study the explicit time dependence of molecular evolutionary processes and their impact on entropy production. Interpreting the mathematical expressions, we can show that two main contributions affect entropy production of molecular evolution processes which can be identified as mutation and gene transfer effects. Accordingly, our results show that the optimal adaptation of organisms to external conditions in the context of evolutionary processes is driven by principles of minimum entropy production. Such results can also be interpreted as the basis of some previous postulates of the theory of learning. Although our macroscopic approach requires certain simplifications, it allows us to interpret molecular evolutionary processes using thermodynamic descriptions with reference to well-known biological processes.

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来源期刊
Journal of Molecular Evolution
Journal of Molecular Evolution 生物-进化生物学
CiteScore
5.50
自引率
2.60%
发文量
36
审稿时长
3 months
期刊介绍: Journal of Molecular Evolution covers experimental, computational, and theoretical work aimed at deciphering features of molecular evolution and the processes bearing on these features, from the initial formation of macromolecular systems through their evolution at the molecular level, the co-evolution of their functions in cellular and organismal systems, and their influence on organismal adaptation, speciation, and ecology. Topics addressed include the evolution of informational macromolecules and their relation to more complex levels of biological organization, including populations and taxa, as well as the molecular basis for the evolution of ecological interactions of species and the use of molecular data to infer fundamental processes in evolutionary ecology. This coverage accommodates such subfields as new genome sequences, comparative structural and functional genomics, population genetics, the molecular evolution of development, the evolution of gene regulation and gene interaction networks, and in vitro evolution of DNA and RNA, molecular evolutionary ecology, and the development of methods and theory that enable molecular evolutionary inference, including but not limited to, phylogenetic methods.
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