使用人工数据和基因表达谱的双聚类算法的比较分析

S. Babichev, V. Osypenko, V. Lytvynenko, M. Voronenko, M. Korobchynskyi
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引用次数: 10

摘要

本文介绍了利用人工数据和基因表达谱对双聚类算法有效性进行比较分析的研究。根据仿真结果,提出了内部双聚类质量准则。该准则的变化与Jaccard指数有较高的相关性,对Jaccard指数进行了优化计算,得到了双聚类。提出了基于“集成”方法的双聚类分析技术,作为分步信息处理的结构框图,利用内部双聚类质量准则确定最优的双聚类水平。
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Comparison Analysis of Biclustering Algorithms with the use of Artificial Data and Gene Expression Profiles
The paper presents the research concerning comparison analysis of biclustering algorithms effectiveness with the use of artificial data and gene expression profiles. Internal biclustering quality criterion is proposed as the result of the simulation. The change of this criterion has high correlation with Jaccard index, which was calculated for perfect and obtained biclustering. The technology of bicluster analysis based on “ensemble” method was proposed as the structural block-chart of step-by-step information processing to determine the optimal biclustering level using internal biclustering quality criterion.
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