Predicts the cystein sulfenylation sites in proteins. iSulf-Cys is a predictor which incorporate 14 kinds of physicochemical properties of amino acids. It also showed satisfying performance in the independent testing dataset with area under the curve (AUC) 0.7343 and Mathew correlation coefficient (MCC) 0.3315. Features which were constructed from physicochemical properties and position were carefully analyzed. This online web-sever could become a useful tool for both basic research and drug development in the relevant areas
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).