Skip to main content

Table 1 Performance comparison between our TI method (  r  = 3) and three other programmes: SOMBRERO, MEME and AlignACE

From: An information transmission model for transcription factor binding at regulatory DNA sites

Factor

 

 abf1 

 csre 

 gal4 

 gcn4 

 gcr1 

 hstf 

 mat 

 mcb 

 mig1 

 pho2 

SOMBRERO

FP

0.56

0.727

0.235

0.286

0.69

0.571

0.25

0.645

0.68

0.909

 

FN

0.45

0.25

0.071

0.6

0.222

0.111

0.308

0.083

0.2

0.5

MEME

FP

0.182

0.667

0.167

0.8

0.444

0.75

0.267

0.25

1

1

 

FN

0.55

0.5

0.286

0.92

0.444

0.333

0.154

0.25

1

1

AlignACE

FP

0.375

0.824

0.083

0.444

0.625

0.556

0

0.083

0.909

1

 

FN

0.5

0.25

0.214

0.6

0.333

0.111

0.308

0.083

0.9

1

TI model with

FP

 0 

 0 

 0 

 0.182 

 0.333 

 0 

 0 

 0 

 0 

 0 

25% known TFBS as training set

FN

0.727

0.5

0.643

 0.259 

0.692

0.667

0.526

0.333

0.429

 0.5 

TI model with

FP

 0 

 0.333 

 0 

 0.226 

 0.143 

 0 

0.294

 0 

 0 

 0 

50% known TFBS as training set

FN

0.455

 0 

0.286

 0.037 

0.308

0.5

0.158

 0.083 

0.214

 0.375 

TI model with

FP

 0 

 0 

 0 

 0.25 

0.615

0.783

0.25

 0 

 0 

 0.25 

75% known TFBS as training set

FN

 0.182 

 0 

0.143

 0.037 

 0.077 

 0 

0.158

 0 

 0.143 

 0.125 

TI model with

FP

 0 

 0 

 0 

 0.265 

0.577

 0.526 

0.222

 0 

 0 

 0.571 

100% known TFBS as training set

FN

 0 

 0 

 0 

 0 

 0 

0.167

 0.053 

 0 

 0.071 

 0 

  1. The best performances of the other three programmes are underlined. The performances of our method that are better than the best of the other three programmes are in bold and underlined. The performances that were close to the best of the other three programmes are in bold. The results show that when the proportion of the training set is larger than or equal to 50%, our method achieves the best performance in most cases.