Table 4 |
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|
Classifier performance in predicting GO terms using individual sources of data and some of their combinations using only data from mouse. |
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|
Source |
AUC |
P20R |
||||
|
MF |
BP |
CC |
MF |
BP |
CC |
|
|
|
||||||
|
BLAST |
0.77 |
0.61 |
0.69 |
0.40 |
0.13 |
0.25 |
|
Sequence |
0.83 |
0.65 |
0.76 |
0.41 |
0.14 |
0.26 |
|
|
||||||
|
PPI |
0.78 |
0.80 |
0.81 |
0.33 |
0.25 |
0.43 |
|
Protein-GO term co-mention |
0.78 |
0.75 |
0.79 |
0.24 |
0.17 |
0.33 |
|
Expression |
0.58 |
0.64 |
0.62 |
0.04 |
0.06 |
0.10 |
|
PPI + co-mention |
0.85 |
0.82 |
0.85 |
0.43 |
0.29 |
0.45 |
|
PPI + co-mention + expression |
0.86 |
0.83 |
0.86 |
0.42 |
0.29 |
0.46 |
|
|
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|
BLAST refers to a classifier trained on BLAST scores only; the Sequence entry uses all the sequence-based features. In addition to classifiers trained on PPI, co-mention and expression individually, we also provide results using PPI and co-mention and the combination of all three. |
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|
Sokolov et al. BMC Bioinformatics 2013 14(Suppl 3):S10 doi:10.1186/1471-2105-14-S3-S10 |
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