Discovering 伪 鈥揚atterns from Gene Expression Data
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- 作者：Domingo S. Rodr铆guez-Baena ; Norberto Diaz-Diaz ; Jes煤s S. Aguilar-Ruiz ; Isabel Nepomuceno-Chamorro
- 刊名：Lecture Notes in Computer Science
- 出版时间：2007
- 出版年：2007
- 期刊代码：99_0302-9743
- 类别：cp
- 卷：4881
- 期：1
- 页码：831-839
- 数据来源：sp
摘要
The biclustering techniques have the purpose of finding subsets of genes that show similar activity patterns under a subset of conditions. In this paper we characterize a specific type of pattern, that we have called α–pattern, and present an approach that consists in a new biclustering algorithm specifically designed to find α–patterns, in which the gene expression values evolve across the experimental conditions showing a similar behavior inside a band that ranges from 0 up to a pre–defined threshold called α. The α value guarantees the co–expression among genes. We have tested our method on the Yeast dataset and compared the results to the biclustering algorithms of Cheng & Church (2000) and Aguilar & Divina (2005). Results show that the algorithm finds interesting biclusters, grouping genes with similar behaviors and maintaining a very low mean squared residue.