Prediction of Cell Specific O-GalNAc Glycosylation in Human

• 作者: Kenli Li Taijiao Jiang Yousong Peng Yuanqiang Zou
• 来源期刊: 国际计算机前沿大会会议论文集
• 学科: 社会科学
• 关键词: O-GLYCOSYLATION Cell-specific SVM Computational PREDICTION Word vector
• 年，卷（期）: 2017,（2）
• 页码范围: 65-67
• 页数: 3页
• 分类号: C5

摘要

Glycosylation is one of the most extensive post-translation modifications of proteins. Although lots of computational models have been developed to predict the glycosylation sites, none of them considered the tissue and cell specificity of glycosylation. Here, we built a two-step computational method GlycoCell to predict the cell-specific O-GalNAc glycosylation, the most complex type of O-glycosylation reported so far, in 12 human cell types. The first step predicted whether a site had the potential to be O-glycosylated. The model achieved an accuracy of 0.83. The second step predicted whether a potential glycosite would be O-glycosylated in the given cell type. For 12 cell types, a model was built for each cell type. The accuracies for these models ranged from 0.78 to 0.87. To facilitate the usage of GlycoCell for the public, a web server was built which is available at http://www.biomedcloud.com.cn/GlyoCell/main.htm. It could be useful for investigating the cell-specific O-glycosylation in human.