※ Documentation:
Content | GPS-SUMO 2.0 | GPS-SUMO | SUMOsp 2.0 | SUMOsp |
---|---|---|---|---|
Non-redundant Data Sets | ||||
Sumoylation Sites | 63,716 | 912 | 332 | 239 |
SUMO Substrates | 9,731 | 510 | 197 | 144 |
SIMs | 176 | 137 | 0 | 0 |
SUMO-interacting Proteins | 104 | 80 | 0 | 0 |
Species | 13 | 12 | 9 | 6 |
Data Size | ~7.2 GB | ~30 MB | ~17 MB | ~10 MB |
Algorithms and Functions | ||||
Features | 11 | 1 | 1 | 1 |
SIM Predictor | √ | √ | × | × |
Species-specific Prediction | √ | × | × | × |
PPI Pairs | 27,482 | × | × | × |
3D Structures | 6,428 | × | × | × |
Frequently Asked Questions:
1. Q: How to use GPS-SUMO 2.0 web server?
A:
Please visit GPS-SUMO 2.0 at https://sumo.biocuckoo.cn/online.php.
We provide 5 versions of prediction for users. You can click “here” at “WEB SERVER” page to change the online service mode or just click the following names of predictor:
(1) Online Service (Penalized Logistic Regression): The default web has fast speed and visualization function. We provide 3D structure, statistics and disorder propensity of protein. For Windows and Unix/Linux users, please use the keyboard shortcuts "Ctrl+C & Ctrl+V" to copy and paste your FASTA format sequences into TEXT form for prediction. And for Mac users, please use the keyboard shortcuts "Command+C & Command+V". You could input one primary sequence or multiple proteins' sequences in FASTA format. Then please click on the "Submit" button to run the program. The prediction results will be shown in the prediction form. Again, please click on the ‘Download’ button on the top of the prediction form to save the results in TXT, Excel or ZIP format. If you want to download statistical graphics, please click on the “Export” button.
A:
Yes! Firstly, the fourth-generation GPS (Group-based Prediction System) algorithm was remained in GPS-SUMO 2.0 and more sequence- and structure- based features and deep learning algorithm have been added. The prediction performance was greatly improved against our previous tools. Secondly, we updated options allowing users to predict with protein sequence or identifiers. We also provide the PPI information, sequence WebLogo, 3D structures, links to PTM database and prediction of secondary structure and disorder propensity. The visualization and user-friendless were greatly improved. Thirdly, the training data set of GPS-SUMO 2.0 was updated by searching the scientific literature published before June 2020 and 13 PTM databases, which is the largest amount of training data so far. Thus, the prediction accuracy of GPS-SUMO 2.0 was significantly improved.
3.
Q: There are three thresholds used in your predictor, what do these parameters mean? A:
There are two types of predictors including sumoylation sites or SUMO-interacting motifs, the threshold options only affect the corresponding one. 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 stringencies were chosen for GPS-SUMO. The performance under these three thresholds was presented as follow:
4. Q: I have a few questions which are
not listed above, how can I contact the authors of GPS-SUMO 2.0? A:
Please contact the responding author: Dr. Yu Xue
for details.
5. Q: Can I use GPS-SUMO 2.0 on different browser? A:
Yes, we test our web server on different browsers.
(2) Online Service (Transformer Neural Network): The deep-learning prediction balances the accuracy with speed.
(3) Online Service of Comprehensive Prediction: The comprehensive prediction has all models and annotations of secondary structure and surface accessibility.
(4) Online Service of Species-specific Prediction: We provide 13 species for species-specific prediction. If you want to focus on certain species, you may choose this one.
(5) Online Service of Prediction According to Protein Identifier: If you want to predict with gene name, protein name or UniProt Accession, please choose this one.
Sumoylation
SUMO interaction
Ac
Sn
Sp
MCC
Pr
Ac
Sn
Sp
MCC
Pr
High
76.16%
57.24%
95.08%
0.5652
92.08%
85.83%
67.50%
95.00%
0.6731
87.10%
Medium
78.75%
67.34%
90.16%
0.5906
87.25%
92.50%
97.50%
90.00%
0.8450
82.98%
Low
80.38%
75.76%
85.00%
0.6102
80.38%
90.00%
98.75%
85.62%
0.8046
77.45%
OS Version Chrome Firefox Microsoft Edge Safari Linux Ubuntu 18.04 107.0.5304.107 107.0.1 N/A N/A MacOS HighSierra 107.0.5304.107 107.0.1 N/A 13.1.2 Windows 10 107.0.5304.107 107.0.1 108.0.1462.46 N/A