Selected article for: "node degree and PPI network"
Author: Zheng Zhang; Sifan Ye; Aiping Wu; Taijiao Jiang; Yousong Peng
Title: Prediction of receptorome for human-infecting virome
  • Document date: 2020_2_28
    • ID: 9ruhvpbv_20
    Snippet: Because not all human proteins were observed in the human PPI network used or had observed expressions in the data used, only the human proteins with all three protein features, i.e., the N-glycosylation level, node degree and expression in common human tissues, were used in the modeling. Besides, the sequence redundancy in both human virus receptor proteins and human membrane proteins were removed using CD-HIT (version 4.8.1) (Fu et al., 2012) a.....
    Document: Because not all human proteins were observed in the human PPI network used or had observed expressions in the data used, only the human proteins with all three protein features, i.e., the N-glycosylation level, node degree and expression in common human tissues, were used in the modeling. Besides, the sequence redundancy in both human virus receptor proteins and human membrane proteins were removed using CD-HIT (version 4.8.1) (Fu et al., 2012) at 70% identity level. Finally, a total of 88 human virus receptors and 1,593 human membrane proteins was used in the machine learning modeling.

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