Use of Recurrence Plots to Find Mutations in Deoxyribonucleic Acid Sequences

IF 0.7 4区 数学 Q4 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS
D. E. Rivas-Cisneros
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引用次数: 0

Abstract

This paper examines the use of recurrence plots to find changes in the deoxyribonucleic acid (DNA) sequence. The DNA sequence is entered into the recurrence plot algorithm in codons and not consecutively, in order to make it easier to find the nucleotide change. The results show that the codon arrangement makes it easy to identify two types of mutations, insertion and deletion, by means of the recurrence plot. It is also shown that the recurrence plot of a short codon sequence has a homogeneous structure. Similarly, a comparison is made with the digital signal processing methodology. Some limitations are the number of codons that can be entered into the algorithm because computationally it becomes very slow and matrix issues, which are mentioned in the discussion section.
使用递归图查找脱氧核糖核酸序列的突变
本文探讨了使用递归图来发现脱氧核糖核酸(DNA)序列的变化。DNA序列以密码子的形式输入递归图算法,而不是连续输入,以便更容易发现核苷酸的变化。结果表明,密码子的排列使得通过递归图很容易识别插入和缺失两种类型的突变。结果还表明,短密码子序列的递推图具有同质结构。同样,与数字信号处理方法进行了比较。一些限制是可以输入算法的密码子的数量,因为计算它变得非常慢,矩阵问题,这在讨论部分提到。
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
Advances in Complex Systems
Advances in Complex Systems 综合性期刊-数学跨学科应用
CiteScore
1.40
自引率
0.00%
发文量
121
审稿时长
6-12 weeks
期刊介绍: Advances in Complex Systems aims to provide a unique medium of communication for multidisciplinary approaches, either empirical or theoretical, to the study of complex systems. The latter are seen as systems comprised of multiple interacting components, or agents. Nonlinear feedback processes, stochastic influences, specific conditions for the supply of energy, matter, or information may lead to the emergence of new system qualities on the macroscopic scale that cannot be reduced to the dynamics of the agents. Quantitative approaches to the dynamics of complex systems have to consider a broad range of concepts, from analytical tools, statistical methods and computer simulations to distributed problem solving, learning and adaptation. This is an interdisciplinary enterprise.
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