扰动存在下生物聚合过程的一种精确稳定的过滤显式方案

IF 4.6 2区 数学 Q1 MATHEMATICS, APPLIED
L. Davis, F. Pahlevani, T. S. Rajan
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引用次数: 2

摘要

本文的重点是高转录基因核糖体RNA转录模型的开发、数值模拟和参数分析。受著名的经典lighhill - whitham - richards (LWR)交通流模型的启发,采用线性平流连续体模型来描述DNA转录过程。在这个模型中,假设延伸速度基本上是恒定的,因为RNA聚合酶沿着链移动,通过基因转录的不同阶段。使用线性模型的一个优点是,它允许人们量化延伸速度和流入参数的微小扰动如何影响重要的生物学测量,如基因的平均转录时间(ATT)。每个聚合酶的ATT是单个RNAP通过DNA链所花费的时间。模型模拟的数值处理包括在经典的迎风方案中加入简单的线性时间滤波器,从而引入低复杂度和时间精度的方法。这种改进的方法是模块化的,只需要添加一行代码的最小修改,从而在不增加计算费用的情况下提高准确性。此外,它消除了逆风的过阻尼。推导了新算法的稳定性条件,并通过数值计算证明了该滤波方案的稳定性和收敛性,以及改进的ATT估计。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An Accurate and Stable Filtered Explicit Scheme for Biopolymerization Processes in the Presence of Perturbations
The focus of this paper is the development, numerical simulation and parameter analysis of a model of the transcription of ribosomal RNA in highly transcribed genes. Inspired by the well-known classic Lighthill-Whitham-Richards (LWR) traffic flow model, a linear advection continuum model is used to describe the DNA transcription process. In this model, elongation velocity is assumed to be essentially constant as RNA polymerases move along the strand through different phases of gene transcription. One advantage of using the linear model is that it allows one to quantify how small perturbations in elongation velocity and inflow parameters affect important biology measures such as Average Transcription Time (ATT) for the gene. The ATT per polymerase is the amount of time an individual RNAP spends traveling through the DNA strand. The numerical treatment for model simulations includes introducing a low complexity and time accurate method by adding a simple linear time filter to the classic upwind scheme. This improved method is modular and requires a minimal modification of adding only one line of code resulting in increased accuracy without increased computational expense. In addition, it removes the overdamping of upwind. A stability condition for the new algorithm is derived, and numerical computations illustrate stability and convergence of the filtered scheme as well as improved ATT estimation.
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来源期刊
CiteScore
8.80
自引率
5.00%
发文量
18
审稿时长
6 months
期刊介绍: Applied and Computational Mathematics (ISSN Online: 2328-5613, ISSN Print: 2328-5605) is a prestigious journal that focuses on the field of applied and computational mathematics. It is driven by the computational revolution and places a strong emphasis on innovative applied mathematics with potential for real-world applicability and practicality. The journal caters to a broad audience of applied mathematicians and scientists who are interested in the advancement of mathematical principles and practical aspects of computational mathematics. Researchers from various disciplines can benefit from the diverse range of topics covered in ACM. To ensure the publication of high-quality content, all research articles undergo a rigorous peer review process. This process includes an initial screening by the editors and anonymous evaluation by expert reviewers. This guarantees that only the most valuable and accurate research is published in ACM.
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