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Fuzzy Ensemble Clustering for DNA Microarray Data Analysis

机译:DNA芯片数据分析的模糊集成聚类

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摘要

Two major problems related the unsupervised analysis of gene expression data are represented by the accuracy and reliability of the discovered clusters, and by the biological fact that classes of examples or classes of functionally related genes are sometimes not clearly defined. To face these items, we propose a fuzzy ensemble clustering approach to both improve the accuracy of clustering results and to take into account the inherent fuzziness of biological and bio-medical gene expression data. Preliminary results with DNA microarray data of lymphoma and adeno-carcinoma patients show the effectiveness of the proposed approach.
机译:与基因表达数据的无监督分析有关的两个主要问题由发现的簇的准确性和可靠性以及有时没有明确定义实例类别或功能相关基因类别的生物学事实表示。为了解决这些问题,我们提出了一种模糊集成聚类方法,既可以提高聚类结果的准确性,又可以考虑到生物学和生物医学基因表达数据固有的模糊性。淋巴瘤和腺癌患者的DNA芯片数据初步结果表明了该方法的有效性。

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