Mining of cis-Regulatory Motifs Associated with Tissue-Specific Alternative Splicing

Authors:
Jihye Kim;Sihui Zhao;Brian E. Howard;Steffen Heber
Affiliations:
Bioinformatics Research Center, North Carolina State University, Raleigh, U.S.A. 27606;Bioinformatics Research Center, North Carolina State University, Raleigh, U.S.A. 27606;Bioinformatics Research Center, North Carolina State University, Raleigh, U.S.A. 27606;Bioinformatics Research Center, North Carolina State University, Raleigh, U.S.A. 27606
Venue:
ISBRA '09 Proceedings of the 5th International Symposium on Bioinformatics Research and Applications
Year:
2009

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Abstract

Alternative splicing (AS) is an important post-transcriptional mechanism that can increase protein diversity and affect mRNA stability and translation efficiency. Many studies targeting the regulation of alternative splicing have focused on individual motifs; however, little is known about how such motifs work in concert. In this paper, we use distribution-based quantitative association rule mining to find combinatorial cis -regulatory motifs and to investigate the effect of motif pairs. We also show that motifs that occur in motif pairs typically occur in clusters.