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Biclustering of Expression Microarray Data Using Affinity Propagation

机译:使用亲和传播的表达式微阵列数据的双板

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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:BICLUSTING,即同时聚类基因和样品,表示表达微阵列数据分析中的具有挑战性和重要的研究线。在本文中,我们调查使用亲和传播,流行聚类方法的使用来执行双板。具体地,我们将亲和力传播传递到这对两种方式聚类方案中,这允许使用聚类技术进行双板。通过引入稳定性标准,扩展CTWC方法,使其适应亲和力传播,并通过设计一种方法来自动将稳定的簇耦合到双板中的方法。在合成基准中获得的经验结果,表明我们对现有技术的方法非常竞争,在最坏情况下实现91%的准确性,最佳测试噪音水平的100%精度案件。

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