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RN+: A Novel Biclustering Algorithm for Analysis of Gene Expression Data Using Protein–Protein Interaction Network

机译:RN +:一种使用蛋白质-蛋白质相互作用网络分析基因表达数据的新型聚类算法

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Biclustering is a process of finding groups of genes that behave similarly under a subset of conditions. In this article, we propose an efficient biclustering algorithm, namely RN+, to identify biologically meaningful biclusters in gene expression data. The RN+ algorithm finds biologically meaningful biclusters through a novel gene filtering using protein–protein interaction network, gene searching, gene grouping, and queuing process. It also efficiently removes duplicate biclusters. We tested the proposed RN+ on five real microarray datasets, and compared its performance with seven competitive biclustering algorithms. The experimental results show that RN+ efficiently finds functionally enriched and biologically meaningful biclusters for large gene expression datasets, and outperforms the other tested biclustering algorithms on real datasets.
机译:双聚簇是寻找在一组条件下表现相似的基因组的过程。在本文中,我们提出了一种有效的双聚类算法,即RN +,以识别基因表达数据中具有生物学意义的双聚类。 RN +算法通过使用蛋白质-蛋白质相互作用网络,基因搜索,基因分组和排队过程的新型基因过滤,找到具有生物学意义的双簇。它还可以有效地删除重复的双簇。我们在五个真实的微阵列数据集上测试了建议的RN +,并将其性能与七个竞争性双聚类算法进行了比较。实验结果表明,RN +有效地为大型基因表达数据集找到了功能丰富且具有生物学意义的双聚类,并且在实际数据集上优于其他经过测试的双聚类算法。

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