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Table 5 Parameter settings of algorithms and post-processing investigated in experiments based on the yeast dataset

From: Identification of coherent patterns in gene expression data using an efficient biclustering algorithm and parallel coordinate visualization

Algorithm/post-filtering Parameter settings*
PA ε = 60, N r = 10, N c = 5, P o = 20
PM ε = 0.2, N r = 10, N c = 5, P o = 20
C&C δ = 100, α = 1.2, M = 100
C&C (log) δ = 0.25, α = 1.2, M = 100
ISA t g = 2, t c = 1.0, number of initial sets = 500
OPSM l = 100
xMotifs n s = 10, n d = 1000, s d = 4, p-value = 10-10, α = 0.29, max. number of expression values = 50
Filtering N r = 10, N c = 5, P o = 20
  1. * The definitions of parameters ε, N r , N c , P o and M follow those defined in the experiments on artificial datasets. The other parameters in C&C, ISA, OPSM and xMotifs are as defined in their original publications [1, 12, 32-34].