用基于随机漫步的方法在蛋白质-蛋白质相互作用网络中识别病理性近视相关基因

IF 2.4 3区 生物学 Q3 BIOCHEMICAL RESEARCH METHODS
Jiyu Zhang, Tao Huang, Qiao Sun, Jian Zhang
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引用次数: 0

摘要

背景病理性近视是近视的一种严重变异,超出了与近视相关的典型屈光不正。虽然这种病症有很强的遗传因素,但其复杂的遗传机制仍然难以捉摸。一些基因与病理性近视的发生有关,但其确切作用尚不完全清楚。研究目的本研究旨在确定与病理性近视相关的新基因 方法::我们的研究利用 DisGeNET 发现了 184 个与高度近视相关的基因和 39 个与退化性近视相关的基因。为了发现更多的病理性近视相关基因,我们采用了随机行走与重启算法来研究蛋白质-蛋白质相互作用网络。我们将之前确定的 184 个高度近视基因和 39 个退化性近视基因作为种子节点。结果通过随后的筛选测试,我们剔除了关联性较弱的基因,得到了 103 个新的高度近视基因和 33 个新的退化性近视基因。结论我们证实了某些基因之间的关联,其中有 6 个基因被证实与高度近视和退化性近视都有关联。新发现的基因有助于揭示和了解近视的发病机理。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Identifying Pathological Myopia Associated Genes with A Random Walk- Based Method in Protein-Protein Interaction Network
Background:: Pathological myopia, a severe variant of myopia, extends beyond the typical refractive error associated with nearsightedness. While the condition has a strong genetic component, the intricate mechanisms of inheritance remain elusive. Some genes have been associated with the development of pathological myopia, but their exact roles are not fully understood. Objective:: This study aimed to identify novel genes associated with pathological myopia Methods:: Our study leveraged DisGeNET to identify 184 genes linked with high myopia and 39 genes related to degenerative myopia. To uncover additional pathological myopia-associated genes, we employed the random walk with restart algorithm to investigate the protein-protein interactions network. We used the previously identified 184 high myopia and 39 degenerative myopia genes as seed nodes. Results:: Through subsequent screening tests, we discarded genes with weak associations, yielding 103 new genes for high myopia and 33 for degenerative myopia. Conclusion:: We confirmed the association of certain genes, including six genes that were confirmed to be associated with both high and degenerative myopia. The newly discovered genes are helpful to uncover and understand the pathogenesis of myopia.
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来源期刊
Current Bioinformatics
Current Bioinformatics 生物-生化研究方法
CiteScore
6.60
自引率
2.50%
发文量
77
审稿时长
>12 weeks
期刊介绍: Current Bioinformatics aims to publish all the latest and outstanding developments in bioinformatics. Each issue contains a series of timely, in-depth/mini-reviews, research papers and guest edited thematic issues written by leaders in the field, covering a wide range of the integration of biology with computer and information science. The journal focuses on advances in computational molecular/structural biology, encompassing areas such as computing in biomedicine and genomics, computational proteomics and systems biology, and metabolic pathway engineering. Developments in these fields have direct implications on key issues related to health care, medicine, genetic disorders, development of agricultural products, renewable energy, environmental protection, etc.
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