全基因组的选择字符串表示

Xiaomeng Wu, Guohui Lin
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引用次数: 1

摘要

可用基因组数据量的增加使得在全基因组规模上进行系统发育分析成为可能。然而,如此庞大的数据量在内存消耗和CPU使用方面都带来了计算挑战。本文提出的一个新颖的建议是提取具有生物学意义的序列模式。使用这些模式,整个基因组可以被映射到一个显著的低维空间,并且使用这些表示的后续研究在计算上是可行的。对64种脊椎动物线粒体基因组和99种原核生物全基因组的实验表明,所选择的序列模式在最终系统发育方面具有良好的进化距离。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Selected String Representation for Whole Genomes
The increase in the amount of available genomic data has made phylogenetic analysis possible at the whole genome scale. However, such a huge amount of data imposes computational challenges in both memory consumption and CPU usage. One novel proposal in this paper is to extract sequence patterns that are biologically meaningful. Using these patterns, whole genomes can be mapped into a significantly lower dimensional space and subsequent studies using these representations become computationally feasible. Experiments on two datasets of 64 vertebrate mitochondrial genomes and 99 prokaryote whole genomes demonstrate that the selected sequence patterns result in good quality evolutionary distances in terms of the final phylogeny.
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