A Frequent Pattern Mining Method for Finding Planted (l, d)-motifs of Unknown Length

  • Caiyan Jia
  • Ruqian Lu
  • Lusheng Chen
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6401)


Identification and characterization of gene regulatory binding motifs is one of the fundamental tasks toward systematically understanding the molecular mechanisms of transcriptional regulation. Recently, the problem has been abstracted as the challenge planted (l, d)-motif problem. Previous studies have developed numerous methods to solve the problem. But most of methods need to specify the length l of a motif in advance. In this study, we present an exact and efficient algorithm, called Apriori-Motif, without given l. The algorithm uses breadth first search and prunes the search space quickly by the downward closure property used in Apriori, a classical algorithm of frequent pattern mining. Empirical study shows that Apriori-Motif is better than some existing methods.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Caiyan Jia
    • 1
  • Ruqian Lu
    • 2
    • 3
  • Lusheng Chen
    • 2
  1. 1.Department of Computer ScienceBeijing Jiaotong UniversityBeijingChina
  2. 2.Shanghai Key Lab of Intelligent Information Processing & Department of Computer Science and EngineeringFudan UniversityShanghaiChina
  3. 3.Institute of MathematicsChinese Academy of SciencesBeijingChina

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