Abstract | ||
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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. |
Year | DOI | Venue |
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2013 | 10.1016/j.patrec.2013.03.018 | Pattern Recognition Letters |
Keywords | Field | DocType |
co-regulated gene cluster,down-regulated gene cluster,gene expression data,different gene expression datasets,global similarity,biclustering technique,gene expression,expression pattern,regulation pattern,microarray expression data,biclustering,support,microarray | Single pass,Gene,Microarray,Pattern recognition,Gene expression,Artificial intelligence,Biclustering,Mathematics | Journal |
Volume | Issue | ISSN |
34 | 14 | 0167-8655 |
Citations | PageRank | References |
12 | 0.56 | 32 |
Authors | ||
3 |
Name | Order | Citations | PageRank |
---|---|---|---|
Swarup Roy | 1 | 56 | 12.13 |
Dhruba K. Bhattacharyya | 2 | 226 | 27.72 |
Jugal K. Kalita | 3 | 856 | 62.32 |