Peters, Bjoern

Targets of T Cell Responses to SARS-CoV-2 Coronavirus in Humans with COVID-19 Disease and Unexposed Individuals

Grifoni, A., Weiskopf, D., Ramirez, S. I., Mateus, J., Dan, J. M., Moderbacher, C. R., Rawlings, S. A., Sutherland, A., Premkumar, L., Jadi, R. S., et al. (2020) · Cell

SARS-CoV-2 and COVID-19 Researchvaccines and immunoinformatics approaches

Cited by 3,595

Immunological memory to SARS-CoV-2 assessed for up to 8 months after infection.

Dan, J. M., Mateus, J., Kato, Y., Hastie, K. M., Yu, E. D., Faliti, C. E., Grifoni, A., Ramirez, S. I., Haupt, S., Frazier, A., et al. (2021) · Science

SARS-CoV-2 and COVID-19 ResearchImmune responses and vaccinations

Cited by 2,656

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

Reynisson, B., Alvarez, B., Paul, S., Peters, B., & Nielsen, M. (2020) · Nucleic Acids Research

vaccines and immunoinformatics approachesImmunotherapy and Immune Responses

Cited by 2,361

Antigen-Specific Adaptive Immunity to SARS-CoV-2 in Acute COVID-19 and Associations with Age and Disease Severity

Rydyznski Moderbacher, C., Ramirez, S. I., Dan, J. M., Grifoni, A., Hastie, K. M., Weiskopf, D., Belanger, S., Abbott, R. K., Kim, C., Choi, J., et al. (2020) · Cell

SARS-CoV-2 and COVID-19 ResearchCOVID-19 Clinical Research Studies

Cited by 1,790

Selective and cross-reactive SARS-CoV-2 T cell epitopes in unexposed humans

Mateus, J., Grifoni, A., Tarke, A., Sidney, J., Ramirez, S. I., Dan, J. M., Burger, Z. C., Rawlings, S. A., Smith, D. M., Phillips, E., et al. (2020) · Science

SARS-CoV-2 and COVID-19 Researchvaccines and immunoinformatics approaches

Cited by 1,120

Impact of Genetic Polymorphisms on Human Immune Cell Gene Expression

Schmiedel, B. J., Singh, D., Madrigal, A., Valdovino-Gonzalez, A. G., White, B. M., Zapardiel-Gonzalo, J., Ha, B., Altay, G., Greenbaum, J. A., McVicker, G., et al. (2018) · Cell

Genetic Associations and EpidemiologyGenomics and Chromatin Dynamics

Cited by 867

T cells from patients with Parkinson’s disease recognize α-synuclein peptides

Sulzer, D., Alcalay, R. N., Garretti, F., Cote, L., Kanter, E., Agin-Liebes, J., Liong, C., McMurtrey, C., Hildebrand, W. H., Mao, X., et al. (2017) · Nature

Parkinson's Disease Mechanisms and TreatmentsNeuroinflammation and Neurodegeneration Mechanisms

Cited by 866

HLA class I supertypes: a revised and updated classification

Sidney, J., Peters, B., Frahm, N., Brander, C., & Sette, A. (2008) · BMC Immunology

vaccines and immunoinformatics approachesImmunotherapy and Immune Responses

Cited by 775

Impact of SARS-CoV-2 variants on the total CD4+ and CD8+ T cell reactivity in infected or vaccinated individuals

Tarke, A., Sidney, J., Methot, N., Yu, E. D., Zhang, Y., Dan, J. M., Goodwin, B., Rubiro, P., Sutherland, A., Wang, E., et al. (2021) · Cell Reports Medicine

SARS-CoV-2 and COVID-19 Researchvaccines and immunoinformatics approaches

Cited by 706

The immune epitope database 2.0

Vita, R., Zarebski, L., Greenbaum, J. A., Emami, H., Hoof, I., Salimi, N., Damle, R., Sette, A., & Peters, B. (2010) · Nucleic Acids Research

vaccines and immunoinformatics approachesImmunotherapy and Immune Responses

Cited by 631

Comprehensive analysis of T cell immunodominance and immunoprevalence of SARS-CoV-2 epitopes in COVID-19 cases

Tarke, A., Sidney, J., Kidd, C. K., Dan, J. M., Ramirez, S. I., Yu, E. D., Mateus, J., da Silva Antunes, R., Moore, E., Rubiro, P., et al. (2021) · Cell Reports Medicine

vaccines and immunoinformatics approachesSARS-CoV-2 and COVID-19 Research

Cited by 540

Key parameters of tumor epitope immunogenicity revealed through a consortium approach improve neoantigen prediction

Wells, D. K., van Buuren, M. M., Dang, K. K., Hubbard-Lucey, V. M., Sheehan, K. C. F., Campbell, K. M., Lamb, A., Ward, J. P., Sidney, J., Blazquez, A. B., et al. (2020) · Cell

vaccines and immunoinformatics approachesCancer Immunotherapy and Biomarkers

Cited by 538

IEDB-AR: immune epitope database-analysis resource in 2019

Dhanda, S. K., Mahajan, S., Paul, S., Yan, Z., Kim, H., Jespersen, M. C., Jurtz, V., Andreatta, M., Greenbaum, J. A., Marcatili, P., et al. (2019) · Nucleic Acids Research

vaccines and immunoinformatics approachesImmunotherapy and Immune Responses

Cited by 427

α-Synuclein-specific T cell reactivity is associated with preclinical and early Parkinson’s disease

Lindestam Arlehamn, C. S., Dhanwani, R., Pham, J., Kuan, R., Frazier, A., Rezende Dutra, J., Phillips, E., Mallal, S., Roederer, M., Marder, K. S., et al. (2020) · Nature Communications

Parkinson's Disease Mechanisms and TreatmentsNeuroinflammation and Neurodegeneration Mechanisms

Cited by 386

SARS-CoV-2 human T cell epitopes: Adaptive immune response against COVID-19

Grifoni, A., Sidney, J., Vita, R., Peters, B., Crotty, S., Weiskopf, D., & Sette, A. (2021) · Cell Host & Microbe

vaccines and immunoinformatics approachesSARS-CoV-2 and COVID-19 Research

Cited by 314

BepiPred-3.0: Improved B-cell epitope prediction using protein language models

Clifford, J., Høie, M. H., Nielsen, M., Deleuran, S., Peters, B., & Marcatili, P. (2022) · Protein Science

vaccines and immunoinformatics approachesMachine Learning in Bioinformatics

Cited by 296

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

vaccines and immunoinformatics approachesMachine Learning in Bioinformatics

Cited by 296

The Immune Epitope Database (IEDB): 2024 update

Vita, R., Blazeska, N., Marrama, D., IEDB Curation Team Members, Shackelford, D., Zalman, L., Foos, G., Zarebski, L., Chan, K., Reardon, B., et al. (2025) · Nucleic Acids Research

vaccines and immunoinformatics approachesResearch Data Management Practices

Cited by 274

Precursors of human CD4 + cytotoxic T lymphocytes identified by single-cell transcriptome analysis

Patil, V. S., Madrigal, A., Schmiedel, B. J., Clarke, J., O’Rourke, P., de Silva, A. D., Harris, E., Peters, B., Seumois, G., Weiskopf, D., et al. (2018) · Science Immunology

T-cell and B-cell ImmunologyImmunotherapy and Immune Responses

Cited by 262

Towards a consensus on datasets and evaluation metrics for developing B-cell epitope prediction tools

Greenbaum, J. A., Andersen, P. H., Blythe, M., Bui, H., Cachau, R. E., Crowe, J., Davies, M., Kolaskar, A. S., Lund, O., Morrison, S., et al. (2007) · Journal of Molecular Recognition

vaccines and immunoinformatics approachesMachine Learning in Bioinformatics

Cited by 244

Adaptive Immune Receptor Repertoire Community recommendations for sharing immune-repertoire sequencing data

Community, T. A., Rubelt, F., Busse, C. E., Bukhari, S. A. C., Bürckert, J.-P., Mariotti-Ferrandiz, E., Cowell, L. G., Watson, C. T., Marthandan, N., Faison, W. J., et al. (2017) · Nature Immunology

T-cell and B-cell ImmunologyResearch Data Management Practices

Cited by 178

Selective CD4+ T Cell Help for Antibody Responses to a Large Viral Pathogen: Deterministic Linkage of Specificities

Sette, A., Moutaftsi, M., Moyron-Quiroz, J., McCausland, M. M., Davies, D. H., Johnston, R. J., Peters, B., Rafii-El-Idrissi Benhnia, M., Hoffmann, J., Su, H.-P., et al. (2008) · Immunity

T-cell and B-cell Immunologyvaccines and immunoinformatics approaches

Cited by 168

Antibody specific B-cell epitope predictions: leveraging information from antibody–antigen protein complexes

Jespersen, M. C., Mahajan, S., Peters, B., Nielsen, M., & Marcatili, P. (2019) · Frontiers in Immunology

vaccines and immunoinformatics approachesMonoclonal and Polyclonal Antibodies Research

Cited by 148

17q21 asthma-risk variants switch CTCF binding and regulate IL-2 production by T cells

Schmiedel, B. J., Seumois, G., Samaniego-Castruita, D., Cayford, J., Schulten, V., Chavez, L., Ay, F., Sette, A., Peters, B., & Vijayanand, P. (2016) · Nature Communications

Asthma and respiratory diseasesGenomics and Chromatin Dynamics

Cited by 127