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Welcome to SulfoSite


SulfoSite is to computationally predict sulfation sites within given protein sequences. A representative set of 162 protein tyrosine sufation sites from the Swiss-Port were used to analyze characteristics and to train and test in SulfoSite. Support Vector Machine (SVM) is applied for learning to each group of sequences and accessible surface area (ASA) value surrounding to the sulfation residues.

Citing SulfoSite
W.C. Chang, T.Y. Lee, D.M. Shien, J.B.K. Hsu, J.T. Horng, P.C. Hsu, T.Y. Wang, H.D. Huang and R.L. Pan. (2009) "Incorporating support vector machine for identifying protein tyrosine sulfation sites", Journal of computational chemistry. [PubMed]
Note:SulfoSite can be easily accessed on ExPasy Proteomics Analysis Tools .

>>> Case study I GAST_HUMAN: Gastrin [Precursor]

>>> Case study II

 PSK1_ORYSJ: Phytosulfokines 1 [Precursor]
  

Predicting Protein Tyrosine Sulfation Sites

Paste a single amino acid sequence or several sequences in FASTA format into the field below:


Submit a file (< 2MB) in FASTA format directly from your local disk


Choose which kind of residues you would like to predict:

Tyrosine (Y)  

Prediction Sensitivity:


 

Bid Lab, Institute of Bioinformatics, National Chiao Tung University , Taiwan.
Contact us:bryan@mail.nctu.edu.tw with questions or comments.
Websites:http://SulfoSite.mbc.nctu.edu.tw