T Cell Epitope Prediction and Its Application to Immunotherapy
| Autor: | Sine Reker Hadrup, Paolo Marcatili, Milena Vujović, Annie Borch, Anna-Lisa Schaap-Johansen |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
Models
Molecular Computer science medicine.medical_treatment T cell Immunology Receptors Antigen T-Cell Epitopes T-Lymphocyte neoepitope prediction T-Cell Antigen Receptor Specificity Computational biology Review Neoepitope prediction Epitope Mass Spectrometry epitope prediction Immune system SDG 3 - Good Health and Well-being Antigens Neoplasm Neoplasms medicine Immunology and Allergy Humans Neoantigens Antigen Presentation Base Sequence T-cell receptor Histocompatibility Antigens Class I Computational Biology Immunotherapy Sequence Analysis DNA RC581-607 Cancer treatment medicine.anatomical_structure Epitope prediction Neural Networks Computer Immunologic diseases. Allergy T cell receptor Peptides neoantigens TCR |
| Zdroj: | Frontiers in Immunology Frontiers in Immunology, Vol 12 (2021) Schaap-Johansen, A L, Vujović, M, Borch, A, Hadrup, S R & Marcatili, P 2021, ' T Cell Epitope Prediction and Its Application to Immunotherapy ', Frontiers in Immunology, vol. 12, 712488 . https://doi.org/10.3389/fimmu.2021.712488 |
| ISSN: | 1664-3224 |
| DOI: | 10.3389/fimmu.2021.712488 |
| Popis: | T cells play a crucial role in controlling and driving the immune response with their ability to discriminate peptides derived from healthy as well as pathogenic proteins. In this review, we focus on the currently available computational tools for epitope prediction, with a particular focus on tools aimed at identifying neoepitopes, i.e. cancer-specific peptides and their potential for use in immunotherapy for cancer treatment. This review will cover how these tools work, what kind of data they use, as well as pros and cons in their respective applications. |
| Databáze: | OpenAIRE |
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