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Fundamentals and Methods for T- and B-Cell Epitope Prediction
Open accessAbstract
Adaptive immunity is mediated by T- and B-cells, which are immune cells capable of developing pathogen-specific memory that confers immunological protection. Memory and effector functions of B- and T-cells are predicated on the recognition through specialized receptors of specific targets (antigens) in pathogens. More specifically, B- and T-cells recognize portions within their cognate antigens known as epitopes. There is great interest in identifying epitopes in antigens for a number of practical reasons, including understanding disease etiology, immune monitoring, developing diagnosis assays, and designing epitope-based vaccines. Epitope identification is costly and time-consuming as it requires experimental screening of large arrays of potential epitope candidates. Fortunately, researchers have developed in silico prediction methods that dramatically reduce the burden associated with epitope mapping by decreasing the list of potential epitope candidates for experimental testing. Here, we analyze aspects of antigen recognition by T- and B-cells that are relevant for epitope prediction. Subsequently, we provide a systematic and inclusive review of the most relevant B- and T-cell epitope prediction methods and tools, paying particular attention to their foundations.
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Improving B-cell epitope prediction and its application to global antibody–antigen docking
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Cited by
Immunomodulatory Effects of Probiotics on Cytokine Profiles
Azad, M. A. K., Sarker, M., & Wan, D. (2018) · BioMed Research International · doi:10.1155/2018/8063647 · Cited by 521
BepiPred ‐3.0: Improved B‐cell epitope prediction using protein language models
Clifford, J. N., Høie, M. H., Deleuran, S., Peters, B., Nielsen, M., & Marcatili, P. (2022) · Protein Science · doi:10.1002/pro.4497 · Cited by 296
Immunoinformatics and Vaccine Development: An Overview
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An in silico deep learning approach to multi-epitope vaccine design: a SARS-CoV-2 case study
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Metadata
- Authors
- Sanchez-Trincado, J. L., Gomez-Perosanz, M., & Reche, P. A.
- Venue
- Journal of Immunology Research
- Publisher
- Wiley
- Published
- 2017
- Volume
- 2017
- Pages
- 1-14
- ISSN
- 2314-7156 (ISSN-L)
- 2314-8861
- OpenAlex
- W2777980778
- Cited by
- 674
- References
- 4
- FWCI
- 11.26
- Type
- journal article
- Language
- en
- Open access
- gold
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