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非标准生物信息学 SARS-CoV-2 特征分析。

Non-standard bioinformatics characterization of SARS-CoV-2.

机构信息

Department of Radiological Informatics and Statistics, Medical University of Gdańsk, 80-210, Gdańsk, Poland.

Department of Nuclear Medicine, Medical University of Gdańsk, 80-210, Gdańsk, Poland.

出版信息

Comput Biol Med. 2021 Apr;131:104247. doi: 10.1016/j.compbiomed.2021.104247. Epub 2021 Feb 1.

Abstract

A non-standard bioinformatics method, 4D-Dynamic Representation of DNA/RNA Sequences, aiming at an analysis of the information available in nucleotide databases, has been formulated. The sequences are represented by sets of "material points" in a 4D space - 4D-dynamic graphs. The graphs representing the sequences are treated as "rigid bodies" and characterized by values analogous to the ones used in the classical dynamics. As the graphical representations of the sequences, the projections of the graphs into 2D and 3D spaces are used. The method has been applied to an analysis of the complete genome sequences of the 2019 novel coronavirus. As a result, 2D and 3D classification maps are obtained. The coordinate axes in the maps correspond to the values derived from the exact formulas characterizing the graphs: the coordinates of the centers of mass and the 4D moments of inertia. The points in the maps represent sequences and their coordinates are used as the classifiers. The main result of this work has been derived from the 3D classification maps. The distribution of clusters of points which emerged in these maps, supports the hypothesis that SARS-CoV-2 may have originated in bat and in pangolin. Pilot calculations for Zika virus sequence data prove that the proposed approach is also applicable to a description of time evolution of genome sequences of viruses.

摘要

一种非标准的生物信息学方法,即 DNA/RNA 序列的 4D 动态表示方法,旨在分析核苷酸数据库中的可用信息,已经被提出。序列由 4D 空间中的“物质点”集合表示 - 4D 动态图。表示序列的图被视为“刚体”,并具有类似于经典动力学中使用的值。作为序列的图形表示,将图投影到 2D 和 3D 空间中使用。该方法已应用于对 2019 年新型冠状病毒的全基因组序列的分析。结果得到了 2D 和 3D 分类图。地图中的坐标轴对应于从准确公式中导出的值,这些公式描述了图形:质心的坐标和 4D 惯性矩。地图中的点代表序列,其坐标用作分类器。这项工作的主要结果来自 3D 分类图。这些地图中出现的点簇的分布,支持了 SARS-CoV-2 可能起源于蝙蝠和穿山甲的假设。针对寨卡病毒序列数据的初步计算证明,所提出的方法也适用于描述病毒基因组序列的时间演变。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3f0b/7966820/b9f868a4f977/gr1_lrg.jpg

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