Deep Learning-Enhanced MHC-II Presentation Prediction and Peptidome Deconvolution
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Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-23198-8_17
Reference17 articles.
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3. Barra, C., et al.: Footprints of antigen processing boost MHC class II natural ligand predictions. Genome Med. 10, 84 (2018)
4. Alspach, E., et al.: MHC-II neoantigens shape tumour immunity and response to immunotherapy. Nature 574, 696-+ (2019)
5. Reynisson, B., Alvarez, B., Paul, S., Peters, B., Nielsen, M.: NetMHCpan-4.1 and NetMHCIIpan-4.0: improved predictions of MHC antigen presentation by concurrent motif deconvolution and integration of MS MHC eluted ligand data. Nucleic Acids Res 48, W449–W454 (2020)
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1. Investigating the human and nonobese diabetic mouse MHC class II immunopeptidome using protein language modeling;Bioinformatics;2023-08-01
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