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Biclustering of Expression Microarray Data Using Affinity Propagation

机译:使用亲和力传播表达微阵列数据

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Biclustering, namely simultaneous clustering of genes and samples, represents a challenging and important research line in the expression microarray data analysis. In this paper, we investigate the use of Affinity Propagation, a popular clustering method, to perform biclustering. Specifically, we cast Affinity Propagation into the Couple Two Way Clustering scheme, which allows to use a clustering technique to perform biclustering. We extend the CTWC approach, adapting it to Affinity Propagation, by introducing a stability criterion and by devising an approach to automatically assemble couples of stable clusters into biclusters. Empirical results, obtained in a synthetic benchmark for biclustering, show that our approach is extremely competitive with respect to the state of the art, achieving an accuracy of 91% in the worst case performance and 100% accuracy for all tested noise levels in the best case.
机译:双表达,即基因和样品的同时聚类,是表达微阵列数据分析中具有挑战性和重要的研究领域。在本文中,我们研究了使用亲和传播(一种流行的聚类方法)进行双聚类。具体来说,我们将“亲和传播”转换为“双向耦合”聚类方案,该方案允许使用聚类技术执行双聚类。我们通过引入稳定性标准并设计出一种方法来自动将几对稳定簇组装成双簇,从而扩展了CTWC方法,使其适应于亲和传播。在合成双基准测试基准中获得的经验结果表明,我们的方法相对于现有技术具有极强的竞争力,在最坏情况下的精度达到91%,在所有测试的噪声水平下均达到100%的精度。案件。

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