高效的TF-IDF方法用于无比对DNA序列相似性分析。

IF 2.7 4区 生物学 Q2 BIOCHEMICAL RESEARCH METHODS
Emre Delibaş
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引用次数: 0

摘要

本研究提出了一种开创性的无比对方法来分析DNA序列相似性。该方法将DNA序列表示为n-图,这是一种将术语频率-逆文档频率(TF-IDF)算法应用于基因组数据的技术。这种方法的主要目标是通过确定信息量最大的n-图来提高结果的准确性,同时降低过程的计算成本。本研究采用的方法成功地规避了传统的基于对准和无对准方法的局限性,从而显示出值得称赞的性能水平。该方法在三个不同的数据集上进行了测试,并与AFProject基准系统中的参考系统发育树具有较高的一致性。结果表明,基于tf - idf的相似性矩阵可以有效地捕获系统发育关系,并显著减少处理时间。获得的高准确率证明该方法在大型基因组数据集中提供了可扩展性和鲁棒性的替代方法。该方法具有精度高、计算成本低的优点,在DNA序列相似性分析中具有很大的应用潜力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Efficient TF-IDF method for alignment-free DNA sequence similarity analysis

Efficient TF-IDF method for alignment-free DNA sequence similarity analysis
This study proposes a pioneering alignment-free approach for the analysis of DNA sequence similarity. The method employs the representation of DNA sequences as n-grams, a technique that involves the adaptation of the Term Frequency-Inverse Document Frequency (TF-IDF) algorithm to genomic data. The primary objective of this approach is to enhance the accuracy of the results while concomitantly reducing the computational costs of the process, by ascertaining the most informative n-grams. The approach adopted in this study successfully circumvents the limitations of both traditional alignment-based and alignment-free methods, thereby demonstrating a commendable level of performance. The proposed method was tested on three different datasets and achieved high agreement with reference phylogenetic trees in the AFProject benchmark system. The results demonstrate that TF-IDF-based similarity matrices effectively capture phylogenetic relationships and significantly reduce processing time. The high accuracy rates obtained prove that the method offers a scalable and robust alternative in large genomic datasets. The method demonstrates considerable potential in DNA sequence similarity analysis, exhibiting high accuracy and low computational cost.
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来源期刊
Journal of molecular graphics & modelling
Journal of molecular graphics & modelling 生物-计算机:跨学科应用
CiteScore
5.50
自引率
6.90%
发文量
216
审稿时长
35 days
期刊介绍: The Journal of Molecular Graphics and Modelling is devoted to the publication of papers on the uses of computers in theoretical investigations of molecular structure, function, interaction, and design. The scope of the journal includes all aspects of molecular modeling and computational chemistry, including, for instance, the study of molecular shape and properties, molecular simulations, protein and polymer engineering, drug design, materials design, structure-activity and structure-property relationships, database mining, and compound library design. As a primary research journal, JMGM seeks to bring new knowledge to the attention of our readers. As such, submissions to the journal need to not only report results, but must draw conclusions and explore implications of the work presented. Authors are strongly encouraged to bear this in mind when preparing manuscripts. Routine applications of standard modelling approaches, providing only very limited new scientific insight, will not meet our criteria for publication. Reproducibility of reported calculations is an important issue. Wherever possible, we urge authors to enhance their papers with Supplementary Data, for example, in QSAR studies machine-readable versions of molecular datasets or in the development of new force-field parameters versions of the topology and force field parameter files. Routine applications of existing methods that do not lead to genuinely new insight will not be considered.
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