|
The prediction accuracy tested on ECRDB62A set. |
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| Algorithm |
nPC |
nSn |
nSp |
sPC |
sSn |
sSp |
|
|
||||||
| BP-MD a) |
0.183 |
0.215 |
0.280 |
0.303 |
0.428 |
0.407 |
| AL-BP-MD |
0.213 |
0.262 |
0.296 |
0.324 |
0.456 |
0.437 |
| AL-BP-MD-MS |
0.209 |
0.255 |
0.293 |
0.321 |
0.423 |
0.446 |
| AL-BP-MD-ME-MS |
0.197 |
0.238 |
0.286 |
0.316 |
0.438 |
0.437 |
|
|
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| AlignACE |
0.141 |
0.218 |
0.171 |
0.264 |
0.351 |
0.396 |
| BioProspector |
0.174 |
0.205 |
0.268 |
0.287 |
0.415 |
0.369 |
| MDScan |
0.146 |
0.174 |
0.223 |
0.244 |
0.345 |
0.349 |
| MEME |
0.160 |
0.260 |
0.190 |
0.300 d) |
0.440 |
0.430 |
| MotifSampler |
0.150 |
0.180 |
0.230 |
0.300 |
0.320 |
0.490 |
|
|
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| RS-AL b) |
0.139 |
0.204 |
0.166 |
0.229 |
0.329 |
0.341 |
| RS-BP |
0.150 |
0.178 |
0.231 |
0.262 |
0.390 |
0.350 |
| RS-MD |
0.107 |
0.125 |
0.169 |
0.170 |
0.254 |
0.271 |
| RS-ME |
0.133 |
0.162 |
0.203 |
0.213 |
0.418 |
0.282 |
| RS-MS |
0.127 |
0.148 |
0.187 |
0.235 |
0.260 |
0.384 |
|
|
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| Random c) |
0.050 |
0.061 |
0.083 |
0.100 |
0.161 |
0.146 |
|
a) The best algorithm among EMD-X (X = 2~5) are compared with component algorithms, b) the multi-restart algorithms, and c) the random algorithms. The best performances in terms of nPC or sPC among algorithms of a same category are highlighted in bold. d) Both MEME and MotifSampler are highlighted because they have the same performance in terms of sPC. | ||||||
Hu et al. BMC Bioinformatics 2006 7:342 doi:10.1186/1471-2105-7-342 |
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