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Combinational logic network for digitally coded gene expression of gastric cancer

机译:组合逻辑网络用于胃癌的数字编码基因表达

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In general, Boolean networks have been addressed in time-series datasets. However, in the recent field of next-generation sequencing-based cancer genomics, cross-sectional data sets having enormous numbers of patients have been accumulated. Here, we deal with representation of cross-sectional datasets using Boolean networks, and specifically, combinational logic network approach. We then applied the approach to a real cancer patient dataset, demonstrating the feasibility of using Boolean networks in graphical representation of cross-sectional datasets.
机译:通常,在时间序列数据集中已解决布尔网络。然而,在最近的下一代序列的癌症基因组学领域中,已经积累了具有大量患者的横截面数据集。在这里,我们处理使用布尔网络的横截面数据集的表示,具体地,组合逻辑网络方法。然后,我们将这种方法应用于真正的癌症患者数据集,展示了在横截面数据集的图形表示中使用布尔网络的可行性。

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