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Table 7 Biclusters

From: Fuzzy association rules for biological data analysis: A case study on yeast

Sup.

Conf.

CF

Association rule

0.0029

0.54

0.45

bicluster = 1 → GO = non-membrane-bound organelle

0.0033

0.61

0.45

bicluster = 1 → GO = nucleus

0.0018

0.68

0.46

bicluster = 2 → length = MEDIUM

0.0022

0.80

0.74

bicluster = 2 → responsiveness = HIGH

0.0012

0.43

0.40

bicluster = 2 → GO = oxidoreductase activity

0.0039

0.65

0.5

bicluster = 3 → GO = nucleus

0.0029

0.48

0.44

bicluster = 3 → GO = DNA metabolism

0.0033

0.81

0.73

bicluster = 4 → length = LOW

0.0036

0.89

0.85

bicluster = 4 → G + C = HIGH

0.0037

0.90

0.89

bicluster = 4 → GO = non-membrane-bound organelle

0.0037

0.90

0.89

bicluster = 4 GO = biosynthesis

0.0037

0.90

0.87

bicluster = 4 → GO = protein complex

0.0035

0.86

0.78

bicluster = 4 → GO = organelle part

0.0035

0.86

0.85

bicluster = 4 → GO = cytosol

0.0035

0.86

0.85

bicluster = 4 → GO = structural molecule activity

0.0107

0.92

0.89

bicluster = 5 → length = HIGH

0.0073

0.63

0.41

bicluster = 5 responsiveness = MEDIUM

0.0019

0.71

0.69

bicluster = 6 → chr = II

0.0017

0.64

0.61

bicluster = 6 → GO = macromolecule biosynthesis

0.0017

0.64

0.62

bicluster = 6 → GO = cytosol

  1. This table shows some rules obtained when looking for relations between the gene expression patterns discovered by the biclustering algorithms and the rest of variables.