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The inference of gene co-expression networks of breast and colon cancer using miRNA-target gene interactions data

机译:利用miRNA-靶标基因相互作用数据推断乳腺癌和结肠癌的基因共表达网络

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Determination of disease related biological processes and the estimation of molecular interactions related to these processes are important to understand the underlying mechanism of diseases. In our study we infer gene co-expression networks of breast and colon cancer using miRNA-target gene interactions. Popular information theory based gene network inference algorithms are utilized to infer gene co-expression networks. Literature data, which is used as validation data in overlap analysis, is used to measure the performances of gene network inference algorithms. According to the results, the precision values of gene co-expression networks of two cancers are close to each other. Our study also states that the relevance calculation methods of gene-gene interactions at the first step of gene network inference algorithms don't change the performance results of gene co-expression networks.
机译:确定与疾病相关的生物过程以及与这些过程相关的分子相互作用的估计对于理解疾病的潜在机制很重要。在我们的研究中,我们使用miRNA-靶基因相互作用来推断乳腺癌和结肠癌的基因共表达网络。基于流行信息论的基因网络推断算法被用来推断基因共表达网络。文献数据在重叠分析中用作验证数据,用于测量基因网络推断算法的性能。根据结果​​,两种癌症的基因共表达网络的精度值彼此接近。我们的研究还指出,基因网络推理算法第一步中的基因-基因相互作用的相关性计算方法不会改变基因共表达网络的性能结果。

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