首页> 外文会议>2018 IEEE International Work Conference on Bioinspired Intelligence >In-Silico Modeling for the Identification of Regulatory Microrna Targets in Epithelial Mesenchymal Transition
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In-Silico Modeling for the Identification of Regulatory Microrna Targets in Epithelial Mesenchymal Transition

机译:上皮间充质转化过程中调控Microrna目标鉴定的硅内建模。

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Epithelial Mesenchymal Transition (EMT) is a common process in many cases of cancer that leads to metastasis. Current understanding of this process has determined that the capability of cancer progression is dependent on this process. Thus, there is great interest on the understanding of the complex pathway regulating this process. Previous work has established a close association between the mir200 family of microRNA and the development of EMT establishing a double negative feedback loop with ZEBl. However, there are no reports studying the quantitative properties of this system to identify the more robust targets to direct an anticancer therapy. In the present work, we constructed an in silico model of EMT in order to identify the main microRNA-regulated factors that contribute to this transition. The resulting model fits the experimental data of the NCI-60 cell line panel, leading to the identification of a strong influence on EMT by mir205a, which could be used as a breakthrough target for EMT regulation.
机译:上皮间质转化(EMT)是导致转移的许多癌症的常见过程。当前对该过程的了解已确定癌症进展的能力取决于该过程。因此,人们对理解调节该过程的复杂途径非常感兴趣。先前的工作已经建立了mir200家族的microRNA与EMT的发展之间的紧密联系,并与ZEB1建立了双重负反馈环。然而,没有报道研究该系统的定量性质以鉴定指导抗癌治疗的更鲁棒的靶标。在当前的工作中,我们构建了一个EMT的计算机模型,以识别导致这种转变的主要microRNA调控因子。所得模型与NCI-60细胞系实验数据吻合,从而确定了mir205a对EMT的强烈影响,可将其用作EMT调控的突破性目标。

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