DocumentCode :
3106805
Title :
Mining Correlation between Motifs and Gene Expression
Author :
Lu, Yi ; Lu, Shiyong ; Platts, Adrian E. ; Krawetz, Stephen A.
Author_Institution :
Wayne State Univ., Detroit, MI
fYear :
2006
fDate :
18-22 Dec. 2006
Firstpage :
986
Lastpage :
990
Abstract :
One of the major challenges in the post-genomic era is to determine all DNA-binding transcription factors (TFs) and their regulatory binding sites (motifs) within the genomes. To discover the relationship between the motifs and changes in gene expression, we propose a new algorithm, co-miner (correlation miner). Correlation rules are generated based on the expression profiles of genes with significant expression change through the time course of gene expression. Thus, we may consider the change in gene expression to be causatively associated with the transcription binding sites in the upstream sequences. In addition, we introduce partition and constraint pushing techniques to improve the performance and demonstrate their effectiveness by our experiments. By applying co-miner to a yeast dataset, the relationships between motifs and gene expression revealed by co-miner are confirmed in the literature.
Keywords :
biology computing; data mining; genetics; Co-Miner; DNA-binding transcription factors; correlation miner; gene expression; mining correlation; motifs; regulatory binding sites; Association rules; Bioinformatics; Bonding; DNA; Data mining; Fungi; Gene expression; Genomics; Partitioning algorithms; Sequences;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Data Mining, 2006. ICDM '06. Sixth International Conference on
Conference_Location :
Hong Kong
ISSN :
1550-4786
Print_ISBN :
0-7695-2701-7
Type :
conf
DOI :
10.1109/ICDM.2006.106
Filename :
4053140
Link To Document :
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