Sequence motif finder using memetic algorithm

BMC Bioinformatics

Table 4 Results achieved by predictors in real datasets experiments

Dataset	Predictor	Precision	Recall	F-Score
CREB	MFMD	0.647±0.024	0.578±0.044	0.611±0.031
	MEME	0	0	0
	GIBBS	0.529	0.473	0.500
CRP	MFMD	0.909±0.039	0.833±0.033	0.869±0.027
	MEME	0.904	0.791	0.844
	GIBBS	0.941	0.666	0.780
HNF1	MFMD	0.772±0.013	0.629±0.032	0.693±0.019
	MEME	0.136	0.111	0.122
	GIBBS	0.500	0.222	0.307
MCB	MFMD	0.999±0.030	0.667±0.042	0.800±0.030
	MEME	0.692	0.750	0.719
	GIBBS	0.750	0.750	0.750
MEF2	MFMD	0.700±0.033	0.823±0.030	0.756±0.024
	MEME	0.705	0.705	0.705
	GIBBS	0.176	0.176	0.176
MYOD	MFMD	0.363±0.016	0.380±0.024	0.372±0.018
	MEME	0.235	0.190	0.210
	GIBBS	0.208	0.238	0.222
NFKB	MFMD	0.667±0.040	0.500±0.099	0.571±0.062
	MEME	0	0	0
	GIBBS	0.667	0.500	0.571
PDR3	MFMD	0.850±0.035	0.944±0.046	0.894±0.034
	MEME	0.653	0.944	0.772
	GIBBS	0.928	0.722	0.812
REB1	MFMD	0.800±0.027	0.600±0.025	0.685±0.021
	MEME	0.333	0.350	0.341
	GIBBS	0.266	0.200	0.228
SRF	MFMD	0.477±0.007	0.583±0.014	0.525±0.008
	MEME	0.440	0.611	0.511
	GIBBS	0.514	0.500	0.507
TBP	MFMD	0.657±0.004	0.768±0.008	0.708±0.006
	MEME	0.578	0.578	0.578
	GIBBS	0.308	0.347	0.326

Some predictors failed to score in these experiments because they found initial positions with a deviation greater than 2. These data are highlighted in bold

ISSN: 1471-2105