Table 1 |
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|
Motif associated with histological grades or prognosis identified based on independent datasets |
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|
aMotif ID |
bReproducibility |
cP value for training data |
dP value for test data |
|
|
|
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|
JSP$NF_Y(20) |
20 |
3.1 × 10-10 |
0.000158 |
|
|
V$NRF1_Q6(10) |
15 |
3.09 × 10-14 |
6.02 × 10-7 |
|
|
motifs associated with histological grades based on the data by Sotiriou et al. |
V$ELK1_02(20) |
12 |
9.25 × 10-26 |
1.41 × 10-6 |
|
DME$CTTCCGSYN(5) |
9 |
5.71 × 10-14 |
6.82 × 10-5 |
|
|
V$E2F1_Q4_01(5) |
7 |
5.71 × 10-15 |
0.002372 |
|
|
|
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|
JSP$NF_Y(10) |
15 |
2.46 × 10-14 |
0.011049 |
|
|
DME$RMSYSSARGCGC(5) |
11 |
4.02 × 10-5 |
0.063412 |
|
|
V$ELK1_02(10) |
10 |
2.03 × 10-16 |
2.08 × 10-7 |
|
|
motifs associated with prognosis based on the data by Sotiriou et al. |
DME$YYYGSGCMYGCG(5) |
8 |
1.65 × 10-9 |
0.008054 |
|
V$E2F1_Q4_01(10) |
8 |
1.05 × 10-17 |
2.37 × 10-5 |
|
|
V$IRF_Q6_01(10) |
7 |
2.06 × 10-8 |
0.000152 |
|
|
DME$NMSTTCYKSYR(5) |
6 |
0.000669 |
0.084446 |
|
|
V$NRF1_Q6(20) |
6 |
9.02 × 10-22 |
1.31 × 10-6 |
|
|
|
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|
JSP$NF_Y(20) |
22 |
5.93 × 10-8 |
0.01116 |
|
|
motifs associated with histological grades based on the data by Pawitan et al. |
V$E2F1_Q4_01(5) |
10 |
6.56 × 10-7 |
0.049423 |
|
DME$RCRKGCGCAVN(5) |
6 |
5.71 × 10-8 |
0.060899 |
|
|
V$E2F1_Q4_01(15) |
6 |
9.59 × 10-6 |
0.017285 |
|
|
|
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|
V$ELK1_02(20) |
16 |
1.26 × 10-27 |
6.13 × 10-12 |
|
|
V$NRF1_Q6(15) |
11 |
9.2 × 10-23 |
3.89 × 10-7 |
|
|
motifs associated with prognosis based on the data by Pawitan et al. |
V$NRF1_Q6(20) |
11 |
4.31 × 10-22 |
2.49 × 10-7 |
|
V$ELK1_02(15) |
9 |
1.63 × 10-25 |
6.41 × 10-11 |
|
|
DME$RCGCHKGCGY(5) |
6 |
3.23 × 10-20 |
4.8 × 10-6 |
|
|
|
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|
aIDs starting from "V$", "JSP$", and "DME$" Motifs denote motifs from the TRANSFAC database, the JASPAR database, and our DME analysis, respectively, followed by values of the threshold parameter for motif searches in parentheses. bThe number of appearances of sequence feature in 30 searches with bootstrap resampling. cdP values calculated by Wilcoxon rank sum tests for training and test data, respectively. |
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|
Niida et al. BMC Bioinformatics 2008 9:404 doi:10.1186/1471-2105-9-404 |
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