Selected article for: "combinatorial library and percentile rank"

Author: Srivastava, Sukrit; Kamthania, Mohit; Singh, Soni; Saxena, Ajay K; Sharma, Nishi
Title: Structural basis of development of multi-epitope vaccine against Middle East respiratory syndrome using in silico approach
  • Document date: 2018_11_21
  • ID: 33h22ikl_10
    Snippet: To screen HTL epitopes, the IEDB tool "MHC-II Binding Predictions" (http://tools.iedb.org/mhcii/) was used. The percentile rank for each peptide is generated by the combination of three methods (Combinatorial Library, SMM-align, and Sturniolo) by comparing the score of peptide against the scores of other random five million 15-mer peptides from the SwissProt database. [27] [28] [29] [30] The rank for the Consensus method was generated by the medi.....
    Document: To screen HTL epitopes, the IEDB tool "MHC-II Binding Predictions" (http://tools.iedb.org/mhcii/) was used. The percentile rank for each peptide is generated by the combination of three methods (Combinatorial Library, SMM-align, and Sturniolo) by comparing the score of peptide against the scores of other random five million 15-mer peptides from the SwissProt database. [27] [28] [29] [30] The rank for the Consensus method was generated by the median percentile rank of the three methods.

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