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

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.