Improved Visualization Method of DNA Sequences and its Application in Phylogenetic Analysis.

IF 1.6 4区医学 Q4 BIOCHEMICAL RESEARCH METHODS

Combinatorial chemistry & high throughput screening Pub Date : 2025-07-01 DOI:10.2174/0113862073379972250612103433

Li Dong, Xinyang Jiang, Yong Liu, Yunlong Gao, Yan Yang

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引用次数: 0

Abstract

Introduction: With a large number of species' genomes assembled, sequence comparison has become an effective method for further studying biological classification and evolution. Traditional sequence alignment relies on predefined scoring functions, but it is computationally intensive and lacks molecular justification for scoring the differences between sequences. Therefore, we have developed a graphical representation method for DNA sequences to facilitate better sequence comparison and evolutionary analysis.

Method: In this article, we introduce a novel method for representing DNA sequences using three-dimensional (3D) graphics. This method possesses two significant properties: (1) the graphical representation is acyclic; (2) each DNA sequence maintains a bijective relationship with its graphical representation.

Result: Leveraging this proposed visualization method, we computed the corresponding ALE index for any DNA sequence by converting it into an L/L matrix and constructed a 12-dimensional feature vector.

Conclusion: The feasibility of our proposed method has been validated through the construction of phylogenetic trees in four test sets: terrestrial vertebrates, hantavirus, fish and Japanese encephalitis virus.

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改进的DNA序列可视化方法及其在系统发育分析中的应用。

随着大量物种基因组的组装，序列比较已成为进一步研究生物分类和进化的有效方法。传统的序列比对依赖于预定义的评分函数，但它计算量大，并且缺乏对序列之间差异进行评分的分子依据。因此，我们开发了一种DNA序列的图形表示方法，以便更好地进行序列比较和进化分析。方法：在这篇文章中，我们介绍了一种用三维（3D）图形表示DNA序列的新方法。该方法具有两个重要的性质：(1)图形表示是无循环的；(2)每个DNA序列与其图形表示保持双向关系。结果：利用所提出的可视化方法，我们将任意DNA序列转换为L/L矩阵，计算出相应的ALE指数，并构建了一个12维特征向量。结论：通过建立陆生脊椎动物、汉坦病毒、鱼类和乙型脑炎病毒4个测试集的系统发生树，验证了该方法的可行性。

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

Combinatorial chemistry & high throughput screening 化学-生化研究方法

CiteScore

3.10

自引率

5.60%

发文量

327

审稿时长

7.5 months

期刊介绍： Combinatorial Chemistry & High Throughput Screening (CCHTS) publishes full length original research articles and reviews/mini-reviews dealing with various topics related to chemical biology (High Throughput Screening, Combinatorial Chemistry, Chemoinformatics, Laboratory Automation and Compound management) in advancing drug discovery research. Original research articles and reviews in the following areas are of special interest to the readers of this journal: Target identification and validation Assay design, development, miniaturization and comparison High throughput/high content/in silico screening and associated technologies Label-free detection technologies and applications Stem cell technologies Biomarkers ADMET/PK/PD methodologies and screening Probe discovery and development, hit to lead optimization Combinatorial chemistry (e.g. small molecules, peptide, nucleic acid or phage display libraries) Chemical library design and chemical diversity Chemo/bio-informatics, data mining Compound management Pharmacognosy Natural Products Research (Chemistry, Biology and Pharmacology of Natural Products) Natural Product Analytical Studies Bipharmaceutical studies of Natural products Drug repurposing Data management and statistical analysis Laboratory automation, robotics, microfluidics, signal detection technologies Current & Future Institutional Research Profile Technology transfer, legal and licensing issues Patents.