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

  • Jihye Kim
  • Sihui Zhao
  • Brian E. Howard
  • Steffen Heber
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5542)

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.

Keywords

Alternative splicing cis-regulatory motifs association rule mining quantitative association rule mining 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Jihye Kim
    • 1
  • Sihui Zhao
    • 1
  • Brian E. Howard
    • 1
  • Steffen Heber
    • 1
  1. 1.Bioinformatics Research CenterNorth Carolina State UniversityRaleighU.S.A.

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