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A NEW CLUSTERING METHOD AND ITS APPLICATION TO PROTEOMIC PROFILING FOR COLON CANCER

机译:一种新的聚类方法及其在结肠癌蛋白质组学中的应用

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摘要

In this paper, we introduce a new clustering method: quasi-clique merger, and its associated data pretreatment programs. This program constructs non-binary hierarchical trees with much smaller number of clusters in the outputs. And overlapping clusters are also allowed in the outputs. We applied this new method to cluster 60 human cancer cell lines (the NCI-60) using the previously identified proteomic determinants for chemosensitivity of 5-Fluorouracil (5-FU). All colon cancer cell lines were aggregated into a single cluster, indicating that the eight proteomic markers are potential diagnostic markers of colon cancer. The results based on the new clustering method have surpassed those based on previous methods on the same datasets.
机译:在本文中,我们介绍了一种新的聚类方法:准自然合并及其相关的数据预处理程序。该程序构建的非二进制层次树的输出中的簇数要少得多。并且在输出中也允许重叠的群集。我们使用这种先前确定的蛋白质组学决定因素对5-氟尿嘧啶(5-FU)的化学敏感性,将这种新方法应用于60个人类癌细胞系(NCI-60)的群集。所有结肠癌细胞系均聚集到单个簇中,表明这八个蛋白质组学标记物是结肠癌的潜在诊断标记物。在相同的数据集上,基于新聚类方法的结果已经超过了基于先前方法的结果。

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