Selected article for: "immune response and prediction system"
Author: Saba Ismail; Sajjad Ahmad; Syed Sikander Azam
Title: Immuno-informatics Characterization SARS-CoV-2 Spike Glycoprotein for Prioritization of Epitope based Multivalent Peptide Vaccine
  • Document date: 2020_4_12
    • ID: 3jmo35jc_4
    Snippet: Immunogenic potential of the MEPVC was conducted in silico using C-ImmSim server [58, 59] . The server used machine learning techniques along with position-specific scoring matrix (PSSM) for prediction of the host immune system response to the antigen. The immune system responds from three mammalian anatomical regions: bone marrow, lymph nodes and thymus. The input parameters for the immune simulations are as follows: number of steps (100), volum.....
    Document: Immunogenic potential of the MEPVC was conducted in silico using C-ImmSim server [58, 59] . The server used machine learning techniques along with position-specific scoring matrix (PSSM) for prediction of the host immune system response to the antigen. The immune system responds from three mammalian anatomical regions: bone marrow, lymph nodes and thymus. The input parameters for the immune simulations are as follows: number of steps (100), volume (10), random seed (12345), HLA (A0101, A0101, B0702, B0702, DRB1_0101, DRB1_0101), number of injection set to 1. The rest of parameters were treated as default.

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