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Potential Activated Pathways Related to Progress of Bladder Cancer Explored by Protein Networks with Gene Expression Changes

机译:与基因表达的蛋白质网络探索的膀胱癌进展相关的潜在活性途径

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Cell signaling pathway is an important facet of biological life. The integration of protein interaction and gene expression data is suitable to uncover the regulation of pathway. However, these methods are still confined to a partial region of large-scale genomics and whole-proteomics. In previous studies for this topic, researches usually focused on the gene level or some limited groups, thus several cancer-related genes cannot appear to known pathway maps. This study presents an approach to finding potential fragments of activated pathways around known pathways between the different stages of cancers. We used a maximum score-based function that integrates genomics and proteomics information. The quantification of the strength of gene expression change was implemented and the global status pathway maps were illustrated. The resulting map shows a possible correspondence between known pathway and cancer-related genes that are not on the known pathway. Comparing diverse status pathway map reveals a global change of diverse disease states pathway level. In this study, the data of bladder cancer was analyzed to explain which potential fragments of pathway play important role at different cancer stages. The insight we gain from the pathway map of different disease statuses helps us to understand the progress of cancer.
机译:细胞信号传导途径是生物学生命的重要面。蛋白质相互作用和基因表达数据的整合适用于揭示途径的调节。然而,这些方法仍然限于大规模基因组学和全蛋白质组学的部分地区。在此主题的先前研究中,通常专注于基因水平或一些有限的群体的研究,因此几种癌症相关基因不能出现已知的途径图。该研究提出了一种方法来寻找癌症的不同阶段之间已知途径的潜在途径的潜在片段。我们使用了最大的基于分数的函数,可以集成基因组学和蛋白质组学信息。实施了基因表达变化强度的定量,并说明了全局地位途径图。所得到的图显示了未在已知途径上的已知途径与癌症相关基因之间的可能对应关系。比较各种状态途径地图揭示了各种疾病状态途径水平的全局变化。在这项研究中,分析了膀胱癌的数据,解释了哪种潜在的途径在不同癌症阶段起着重要作用。我们从不同疾病状态的途径地图获得的洞察力有助于我们了解癌症的进步。

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