Table 5 Performance comparisons for USW, AKL, ALLR, PCC, CS, and MOTIFSIM for the predicted motifs in the collection. The number of motifs that were correctly identified by each method per sequence dataset is listed. The percentage of motifs that were correctly identified by each method per dataset was also calculated
Sequence Dataset | Number of Motifs Correctly Identified | Â | % of Motifs Correctly Identified | ||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
USW | AKL | ALLR | PCC | CS | MOTIFSIM | Total # of Tools | USW | AKL | ALLR | PCC | CS | MOTIFSIM | |
hm08m | 0 | 0 | 0 | 0 | 0 | 1 | 12 | 0% | 0% | 0% | 0% | 0% | 8% |
hm17g | 2 | 0 | 0 | 0 | 3 | 2 | 5 | 40% | 0% | 0% | 0% | 60% | 40% |
hm22m | 1 | 0 | 0 | 0 | 2 | 1 | 10 | 10% | 0% | 0% | 0% | 20% | 10% |
mus04m | 0 | 0 | 0 | 0 | 0 | 2 | 12 | 0% | 0% | 0% | 0% | 0% | 17% |
mus06g | 1 | 1 | 0 | 0 | 1 | 2 | 13 | 8% | 8% | 0% | 0% | 8% | 15% |
mus10g | 3 | 0 | 0 | 0 | 0 | 5 | 11 | 27% | 0% | 0% | 0% | 0% | 45% |
mus11m | 2 | 0 | 0 | 0 | 0 | 3 | 11 | 18% | 0% | 0% | 0% | 0% | 27% |
yst02g | 6 | 0 | 0 | 0 | 7 | 6 | 11 | 55% | 0% | 0% | 0% | 64% | 55% |
yst03m | 3 | 0 | 0 | 0 | 1 | 9 | 13 | 23% | 0% | 0% | 0% | 8% | 69% |
yst06g | 5 | 0 | 0 | 0 | 2 | 3 | 11 | 45% | 0% | 0% | 0% | 18% | 27% |
yst09g | 2 | 0 | 0 | 0 | 1 | 1 | 3 | 67% | 0% | 0% | 0% | 33% | 33% |
Total | 25 | 1 | 0 | 0 | 17 | 35 | 112 | 22% | 1% | 0% | 0% | 15% | 31% |