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Cohen's Conjecture, Howard's Hypothesis, and Ptashne's Ptruth: an exploration of the relationship between affinity and specificity

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Chimeric 2 microglobulin/CD3 polypeptides expressed in T cells convert MHC class I peptide ligands into T cell activation receptors: a potential tool for specific targeting of pathogenic CD8+ T cells

Margalit, A. (2003) · International Immunology · doi:10.1093/intimm/dxg136 · Cited by 26

Synthetic Biology: Immunotherapy by Design

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HIV peptidome-wide association study reveals patient-specific epitope repertoires associated with HIV control

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One-step generation of monoclonal B cell receptor mice capable of isotype switching and somatic hypermutation

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The somatically generated portion of T cell receptor CDR3α contributes to the MHC allele specificity of the T cell receptor

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Stress-testing the relationship between T cell receptor/peptide-MHC affinity and cross-reactivity using peptide velcro

Gee, M. H., Sibener, L. V., Birnbaum, M. E., Jude, K. M., Yang, X., Fernandes, R. A., Mendoza, J. L., Glassman, C. R., & García, K. C. (2018) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1802746115 · Cited by 23

Ex vivo evolution of human antibodies by CRISPR-X: from a naive B cell repertoire to affinity matured antibodies

Devilder, M., Moyon, M., Gautreau‐Rolland, L., Navet, B., Perroteau, J., Delbos, F., Gesnel, M.-C., Breathnach, R., & Saulquin, X. (2019) · BMC Biotechnology · doi:10.1186/s12896-019-0504-z · Cited by 23

The intersection of affinity and specificity in the development and optimization of T cell receptor based therapeutics

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Activation of the MEK-ERK Pathway Is Necessary but Not Sufficient for Breaking Central B Cell Tolerance

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AbPredict 2: a server for accurate and unstrained structure prediction of antibody variable domains

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Peptide based diagnostics: Are random-sequence peptides more useful than tiling proteome sequences?

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Higher Throughput Methods of Identifying T Cell Epitopes for Studying Outcomes of Altered Antigen Processing and Presentation

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ImmuneBuilder: Deep-Learning models for predicting the structures of immune proteins

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Computational approaches to therapeutic antibody design: established methods and emerging trends

Norman, R. A., Ambrosetti, F., Bonvin, A. M. J. J., Colwell, L. J., Kelm, S., Kumar, S., & Krawczyk, K. (2020) · Briefings in Bioinformatics · doi:10.1093/bib/bbz095 · Cited by 219

A compact vocabulary of paratope-epitope interactions enables predictability of antibody-antigen binding

Akbar, R., Robert, P. A., Pavlović, M., Jeliazkov, J. R., Snapkov, I., Slabodkin, A., Weber, C. R., Scheffer, L., Miho, E., Haff, I. H., et al. (2021) · Cell Reports · doi:10.1016/j.celrep.2021.108856 · Cited by 191

Progress and challenges for the machine learning-based design of fit-for-purpose monoclonal antibodies

Akbar, R., Bashour, H., Rawat, P., Robert, P. A., Smorodina, E., Cotet, T., Karlsen, K. F., Frank, R., Mehta, B. B., Vu, M. H., et al. (2022) · mAbs · doi:10.1080/19420862.2021.2008790 · Cited by 121

Modern Hopfield Networks and Attention for Immune Repertoire ClassificationPreprint

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Mining adaptive immune receptor repertoires for biological and clinical information using machine learning

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Engineering immunity with quantitative tools

Jewell, C. M., & Gray, J. J. (2019) · Molecular Systems Design & Engineering · doi:10.1039/c9me90024a

The Adaptive Immune System

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Immune Literacy: Reading, Writing, and Editing Adaptive Immunity

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Immune engineering: From systems immunology to engineering immunity

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