iSulf-Cys statistics
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S-sulfenylation site prediction
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iSulf-Cys specifications
Information
| Unique identifier | OMICS_15002 |
|---|---|
| Name | iSulf-Cys |
| Interface | Web user interface |
| Restrictions to use | None |
| Input data | Query protein sequences. |
| Input format | FASTA |
| Programming languages | Java |
| Computer skills | Basic |
| Stability | Stable |
| Maintained | Yes |
Maintainer
- person_outline Yan Xu
Publication for iSulf-Cys
library_books
ISulf-Cys: Prediction of S-sulfenylation Sites in Proteins with Physicochemical Properties of Amino Acids.
2016 PLoS One
PMCID: 4841585
PMID: 27104833
DOI: 10.1371/journal.pone.0154237
iSulf-Cys citation
library_books
CIPPN: computational identification of protein pupylation sites by using neural network
2017
Oncotarget
PMCID: 5752488
PMID: 29312575
DOI: 10.18632/oncotarget.22335
[…] 2 versions (GPS2.2) algorithm, Liu and their coworkers introduced the first predictor for the prediction of the pupylation sites in the field of bioinformatics []. Yan Xu and their team developed the iSulf-Cys algorithm to identify the S-sulfenylation Sites with the physicochemical properties of amino acid residues [, ]. Tung developed a predictor, which is named the iPUP server, utilizing the com […]
iSulf-Cys institution(s)
Department of Information and Computer Science, University of Science and Technology Beijing, Beijing, China; Institute of Applied Mathematics, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, China
iSulf-Cys funding source(s)
This work was supported by grants from the Natural Science Foundation of China (11301024, 31171263, 81272578, and J1103514) and the Fundamental Research Funds for the Central Universities (No. FRF-BR-15-075A).
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