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Discovering hidden relationships between renal diseases and regulated genes through 3D network visualizations

机译:通过3D网络可视化发现肾脏疾病和调控基因之间的隐藏关系

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Background In a recent study, two-dimensional (2D) network layouts were used to visualize and quantitatively analyze the relationship between chronic renal diseases and regulated genes. The results revealed complex relationships between disease type, gene specificity, and gene regulation type, which led to important insights about the underlying biological pathways. Here we describe an attempt to extend our understanding of these complex relationships by reanalyzing the data using three-dimensional (3D) network layouts, displayed through 2D and 3D viewing methods. Findings The 3D network layout (displayed through the 3D viewing method) revealed that genes implicated in many diseases (non-specific genes) tended to be predominantly down-regulated, whereas genes regulated in a few diseases (disease-specific genes) tended to be up-regulated. This new global relationship was quantitatively validated through comparison to 1000 random permutations of networks of the same size and distribution. Our new finding appeared to be the result of using specific features of the 3D viewing method to analyze the 3D renal network. Conclusions The global relationship between gene regulation and gene specificity is the first clue from human studies that there exist common mechanisms across several renal diseases, which suggest hypotheses for the underlying mechanisms. Furthermore, the study suggests hypotheses for why the 3D visualization helped to make salient a new regularity that was difficult to detect in 2D. Future research that tests these hypotheses should enable a more systematic understanding of when and how to use 3D network visualizations to reveal complex regularities in biological networks.
机译:背景技术在最近的一项研究中,二维(2D)网络布局用于可视化和定量分析慢性肾脏疾病与调控基因之间的关系。结果揭示了疾病类型,基因特异性和基因调控类型之间的复杂关系,这导致了对潜在生物学途径的重要见解。在这里,我们描述了一种尝试,即通过使用3D(3D)网络布局(通过2D和3D查看方法显示)重新分析数据来扩展我们对这些复杂关系的理解。调查结果3D网络布局(通过3D观看方法显示)显示,与许多疾病有关的基因(非特异性基因)倾向于主要下调,而在少数疾病中涉及的基因(疾病特异性基因)则倾向于下调。上调。通过与1000个相同大小和分布的网络的随机排列进行比较,对这种新的全局关系进行了定量验证。我们的新发现似乎是使用3D观看方法的特定功能来分析3D肾网络的结果。结论基因调控与基因特异性之间的全球关系是人类研究的第一个线索,即在几种肾脏疾病中存在共同的机制,这为潜在的机制提出了假设。此外,该研究提出了关于3D可视化为何有助于使显着性成为2D难以检测到的新规律性的假设。检验这些假设的未来研究应该能够更系统地了解何时以及如何使用3D网络可视化来揭示生物网络中的复杂规律。

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