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引用次数: 31

摘要

寻找共调控基因群的问题被认为是基因表达数据分析中的主要挑战之一。双聚类可以看作是分析这些数据的主要技术之一。双聚类是一种优于传统聚类技术的无监督聚类技术,因为它可以同时对基因和条件进行分组。一个基因或状况可能属于多个双聚类,因此涉及多个生物功能或过程。本文首先介绍了双聚类的一些定义及其数学模型,然后根据它们所能找到的双聚类的类型回顾了一些双聚类技术;最后介绍了一组验证措施来验证强调生物措施的双聚类技术。
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On biclustering of gene expression data
The problem of finding groups of co-regulated genes is considered one of the major challenges in the analysis of gene expression data. Biclustering may be considered as one of the main techniques to analyze these data. Biclustering is a non-supervised technique outperforms the traditional clustering techniques because it can group both genes and conditions in the same time. A gene or condition may belong to more than one bicluster and hence to more than biological function or process. In this survey, we introduced some definitions of the biclustering with its mathematical model after that we reviewed some biclustering techniques based on the type of biclusters they can find; finally a set of validation measures were introduced to validate the biclustering techniques emphasizing the biological measures.
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