Skip to main content
. 2013 Sep 26;42(1):417–429. doi: 10.1093/nar/gkt856

Table 3.

Overrepresentation of functional motifs in the predicted targets

Bank Name Proteome Targets Overrepresentation P-value Function
Panther PTHR19959:SF16 59 22 4.00 5.62E-09 Kinesin
Fprint PR00381 38 17 4.80 1.20E-08 Kinesin light chain
Panther PTHR19959 80 23 3.08 6.27E-07 Structural constituent of cytoskeleton
Pfam PF00931 31 12 4.15 1.09E-05 NB-ARC domain
superfamily SSF48452 231 41 1.90 4.23E-05 TPR-like superfamily
Pfam PF07721 21 9 4.59 5.43E-05 Tetratricopeptide repeat
Smart SM00028 124 26 2.25 6.43E-05 Tetratricopeptide repeats
Prosite PS50293 166 31 2.00 1.35E-04 TPR repeat region
Pfam PF00515 61 14 2.46 1.21E-03 Tetratricopeptide repeat
Gene3D G3DSA:1.25.40.10 326 45 1.48 4.94E-03 TPR-like_helical
Pfam PF08241 49 12 2.63 1.46E-03 Methyltransferase
Panther PTHR10108 33 9 2.92 2.55E-03 Methyltransferase
Pfam PF00066 31 9 3.11 1.58E-03 LNR domain
Prosite PS00120 13 5 4.12 4.76E-03 Lipases, serine active site
Gene3D G3DSA:2.160.20.10 98 17 1.86 8.82E-03 Pectin lyase-like

Motifs were grouped by similar function, and groups were sorted by ascending best P-value. ‘Proteome’ and ‘Targets’ show the number of proteins containing at least one instance of the motif in the whole genome and in the set of targets that we predicted in silico, respectively. The ‘Overrepresentation’ is the ratio of the two previous columns, each normalized to its respective total number of proteins in the set. The P-value is computed using the hypergeometric probability law.