Suppr超能文献

利用特定图灵机对某些产生营养物质的原始细胞的突变和竞争进行建模。

Modeling the Mutation and Competition of Certain Nutrient-Producing Protocells by Means of Specific Turing Machines.

作者信息

Kicsiny Richárd, Hufnagel Levente, Lóczi Lajos, Székely László, Varga Zoltán

机构信息

Hungarian University of Agriculture and Life Sciences, Institute of Mathematics and Basic Science, Department of Mathematics and Modelling.

John Wesley Theological College, Research Institute of Multidisciplinary Ecotheology.

出版信息

Artif Life. 2024 Feb 25;31(1):2-30. doi: 10.1162/artl_a_00463.

Abstract

It is very important to model the behavior of protocells as basic lifelike artificial organisms more and more accurately from the level of genomes to the level of populations. A better understanding of basic protocell communities may help us in describing more complex ecological systems accurately. In this article, we propose a new comprehensive, bilevel mathematical model of a community of three protocell species (one generalist and two specialists). The aim is to achieve a model that is as basic/fundamental as possible while already displaying mutation, selection, and complex population dynamics phenomena (like competitive exclusion and keystone species). At the microlevel of genetic codes, the protocells and their mutations are modeled with Turing machines (TMs). The specialists arise from the generalist by means of mutation. Then the species are put into a common habitat, where, at the macrolevel of populations, they have to compete for the available nutrients, a part of which they themselves can produce. Because of different kinds of mutations, the running times of the species as TMs (algorithms) are different. This feature is passed on to the macrolevel as different reproduction times. At the macrolevel, a discrete-time dynamic model describes the competition. The model displays complex lifelike behavior known from population ecology, including the so-called competitive exclusion principle and the effect of keystone species. In future works, the bilevel model will have a good chance of serving as a simple and useful tool for studying more lifelike phenomena (like evolution) in their pure/abstract form.

摘要

从基因组层面到种群层面,越来越准确地将原细胞的行为建模为基本的类似生命的人工生物体,这非常重要。更好地理解基本的原细胞群落可能有助于我们准确描述更复杂的生态系统。在本文中,我们提出了一个新的综合双层数学模型,用于描述由三种原细胞物种(一种通才物种和两种专才物种)组成的群落。目标是构建一个尽可能基础的模型,同时已经能够展现突变、选择和复杂的种群动态现象(如竞争排斥和关键物种)。在遗传密码的微观层面,原细胞及其突变用图灵机(TMs)进行建模。专才物种通过突变从通才物种中产生。然后将这些物种置于一个共同的栖息地中,在种群的宏观层面,它们必须竞争可用的营养物质,其中一部分营养物质它们自身能够生产。由于存在不同类型的突变,作为图灵机(算法)的物种运行时间各不相同。这一特征在宏观层面表现为不同的繁殖时间。在宏观层面,一个离散时间动态模型描述了这种竞争。该模型展现了种群生态学中已知的复杂的类似生命的行为,包括所谓的竞争排斥原理和关键物种的影响。在未来的工作中,这个双层模型很有可能成为一个简单且有用的工具,用于以纯粹/抽象的形式研究更多类似生命的现象(如进化)。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验