Cargando…
Machine learning optimization of peptides for presentation by class II MHCs
SUMMARY: T cells play a critical role in cellular immune responses to pathogens and cancer and can be activated and expanded by Major Histocompatibility Complex (MHC)-presented antigens contained in peptide vaccines. We present a machine learning method to optimize the presentation of peptides by cl...
Autores principales: | Dai, Zheng, Huisman, Brooke D, Zeng, Haoyang, Carter, Brandon, Jain, Siddhartha, Birnbaum, Michael E, Gifford, David K |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8504626/ https://www.ncbi.nlm.nih.gov/pubmed/33705522 http://dx.doi.org/10.1093/bioinformatics/btab131 |
Ejemplares similares
-
Frequency Patterns of T-Cell Exposed Amino Acid Motifs in Immunoglobulin Heavy Chain Peptides Presented by MHCs
por: Bremel, Robert D., et al.
Publicado: (2014) -
Computationally Optimized SARS-CoV-2 MHC Class I and II Vaccine Formulations Predicted to Target Human Haplotype Distributions
por: Liu, Ge, et al.
Publicado: (2020) -
Repertoire-scale determination of class II MHC peptide binding via yeast display improves antigen prediction
por: Rappazzo, C. Garrett, et al.
Publicado: (2020) -
Insight into Cancer Immunity: MHCs, Immune Cells and Commensal Microbiota
por: Wen, Minting, et al.
Publicado: (2023) -
A high-throughput yeast display approach to profile pathogen proteomes for MHC-II binding
por: Huisman, Brooke D, et al.
Publicado: (2022)