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MaPle: Efficient Enumeration of δ-pClusters

  • Pei et al., MaPle: Efficient enumerating all maximal δ-pClusters. ICDM'03
  • Framework: Same as pattern-growth in frequent pattern mining (based on the downward closure property)
  • For each condition combination J, find the maximal subsets of genes I such that I x J is a δ-pClusters
    • If I x J is not a submatrix of another δ-pClusters
    • then I x J is a maximal δ-pCluster.
  • Algorithm is very similar to mining frequent closed itemsets
  • Additional advantages of δ-pClusters:
    • Due to averaging of δ-cluster, it may contain outliers but still within δ-threshold
    • Computing bi-clusters for scaling patterns, take logarithmic on
      • will lead to the p-score form

\[\frac{d_{xa}/d_{ya}}{d_{xb}/d_{yb}}<\delta \]


Speaker notes:

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