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Pan‐specific prediction of receptor–ligand interaction is conventionally done using machine‐learning methods that integrates information about both receptor and ligand primary sequences. To achieve optimal performance using machine learning, dealing with overfitting and data redundancy is critical. Most often so‐called ligand clustering methods have been used to deal with these issues in the context...
Major histocompatibility complex (MHC) molecules play a key role in cell‐mediated immune responses presenting bounded peptides for recognition by the immune system cells. Several in silico methods have been developed to predict the binding affinity of a given peptide to a specific MHC molecule. One of the current state‐of‐the‐art methods for MHC class I is NetMHCpan, which has a core ingredient for...
A major challenge in epitope‐based vaccine (EV) design stems from the vast genomic variation of pathogens and the diversity of the host cellular immune system. Several computational approaches have been published to assist the selection of potential T cell epitopes for EV design. So far, no thorough comparison between the current methods has been realized. Using human immunodeficiency virus as test...
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