Current Slide

• 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

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