A Spatial Artificial Chemistry Implementation of a Gene Regulatory Network Aimed at Generating Protein Concentration Dynamics

IF 1.6 4区 计算机科学 Q4 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Iliya Miralavy;Wolfgang Banzhaf
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引用次数: 0

Abstract

Gene regulatory networks are networks of interactions in organisms responsible for determining the production levels of proteins and peptides. Mathematical and computational models of gene regulatory networks have been proposed, some of them rather abstract and called artificial regulatory networks. In this contribution, a spatial model for gene regulatory networks is proposed that is biologically more realistic and incorporates an artificial chemistry to realize the interaction between regulatory proteins called the transcription factors and the regulatory sites of simulated genes. The result is a system that is quite robust while able to produce complex dynamics similar to what can be observed in nature. Here an analysis of the impact of the initial states of the system on the produced dynamics is performed, showing that such models are evolvable and can be directed toward producing desired protein dynamics.
旨在生成蛋白质浓度动态的基因调控网络的空间人工化学实现。
基因调控网络是生物体内的相互作用网络,负责决定蛋白质和肽的生产水平。基因调控网络的数学模型和计算模型已被提出,其中一些比较抽象,被称为人工调控网络。本文提出的基因调控网络空间模型更符合生物学实际,并结合了人工化学,以实现称为转录因子的调控蛋白与模拟基因的调控位点之间的相互作用。其结果是一个相当稳健的系统,同时能够产生与自然界中观察到的类似的复杂动态。在这里,我们分析了系统初始状态对所产生动态的影响,表明这种模型是可进化的,并可定向产生所需的蛋白质动态。
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
Artificial Life
Artificial Life 工程技术-计算机:理论方法
CiteScore
4.70
自引率
7.70%
发文量
38
审稿时长
>12 weeks
期刊介绍: Artificial Life, launched in the fall of 1993, has become the unifying forum for the exchange of scientific information on the study of artificial systems that exhibit the behavioral characteristics of natural living systems, through the synthesis or simulation using computational (software), robotic (hardware), and/or physicochemical (wetware) means. Each issue features cutting-edge research on artificial life that advances the state-of-the-art of our knowledge about various aspects of living systems such as: Artificial chemistry and the origins of life Self-assembly, growth, and development Self-replication and self-repair Systems and synthetic biology Perception, cognition, and behavior Embodiment and enactivism Collective behaviors of swarms Evolutionary and ecological dynamics Open-endedness and creativity Social organization and cultural evolution Societal and technological implications Philosophy and aesthetics Applications to biology, medicine, business, education, or entertainment.
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