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CoBi: Pattern Based Co-Regulated Biclustering of Gene Expression Data

机译:CoBi:基于模式的基因表达数据的共同调节聚类

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摘要

Co-regulation is a common phenomenon in gene expression. Finding positively and negatively co-regulated gene clusters from gene expression data is a real need. Existing techniques based on global similarity are unable to detect true up- and down-regulated gene clusters. This paper presents an expression pattern based biclustering technique, CoBi, for grouping both positively and negatively regulated genes from microarray expression data. Regulation pattern and similarity in degree of fluctuation are accounted for while computing similarity between two genes. Unlike traditional biclustering techniques, which use greedy iterative approaches, it uses a BiClust tree that needs single pass over the entire dataset to find a set of biologically relevant biclusters. Biclusters determined from different gene expression datasets by the technique show highly enriched functional categories.
机译:共同调节是基因表达中的常见现象。从基因表达数据中找到正负共同调控的基因簇是真正的需求。基于全局相似性的现有技术无法检测到真正上调和下调的基因簇。本文提出了一种基于表达模式的双聚类技术CoBi,用于将来自微阵列表达数据的正调控和负调控基因进行分组。在计算两个基因之间的相似性时,要考虑调节模式和波动程度的相似性。与使用贪婪迭代方法的传统双聚类技术不同,它使用BiClust树,该树需要遍历整个数据集才能找到一组生物学相关的双聚类。通过该技术从不同基因表达数据集确定的双簇显示高度丰富的功能类别。

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