※ Advanced Services of GPS-SUMO 2.0 

Please click the check box '' to select your predictor, you can see '' before the selected one.

1. GPS-SUMO 2.0 (PLR):  Prediction based on penalized logistic regression with the group-based prediction system feature (Also available at the HOME page). Speed:

2. GPS-SUMO 2.0 (Transformer):  Prediction based on Transformer with the contextual information. Speed:

3. GPS-SUMO 2.0 (All):  Prediction based on all models with all features. Speed:

4. GPS-SUMO 2.0 (Species-specific):  Species-specific prediction based on all models with all features. Speed:

5. GPS-SUMO 2.0 (Comprehensive):  Prediction based on all models with all features and additional annotations of secondary structure and surface accessibility. Speed:

6. GPS-SUMO 2.0 (Stress conditions):   Prediction based on penalized logistic regression, using 39,938 non-redundant SUMOylation sites identified under various stress conditions, such as SUMO protease inhibition, proteasome inhibition and heat shock. Speed:

According to   Sequence(s) in FASTA format    UniProt Accession Number(s)

     Please enter UniProt accession number(s)

H. sapiens M. musculus R. norvegicus
D. rerio D. melanogaster C. elegans
A. thaliana S. cerevisiae B. taurus
G. gallus X. laevis D. discoideum
SUMOylation: SUMO interaction:
Motif Filter

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After GPS-SUMO 2.0 predictor model was well-trained, we performed an evaluation on this model. From the evaluation, three thresholds with High, Medium and Low stringency were chosen for GPS-SUMO 2.0. The performance under these three thresholds was presented as follow:

The performance of GPS-SUMO 2.0 in different thresholds
Threshold SUMOylation SUMO interaction
Ac Sn Sp MCC Pr Ac Sn Sp MCC Pr
High 88.63% 57.45% 95.17% 0.5749 71.39% 94.64% 90.06% 95.17% 0.7551 68.08%
Medium 86.60% 68.24% 90.46% 0.5585 60.00% 90.88% 98.14% 90.05% 0.6823 53.02%
Low 84.33% 75.98% 85.01% 0.5293 51.54% 86.80% 99.38% 85.36% 0.6081 43.72%