Author

B. Carter

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Immunology· 7 Cancer Biology· 1 Ecology· 1 Evolutionary Biology· 1

Signature Assays, Organisms & Methods

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Research Focus:drug response / drug discovery· 5 Assay:proteomics· 5 Organism:human· 4 Approach:machine learning (classical)· 4 Approach:experimental assay· 3 Assay:bulk RNA-seq· 2 Research Focus:cell type annotation· 2 Organism:mouse· 2

Frequent Co-Authors

D. K. Gifford· 7 shared G. Liu· 4 shared M. E. Birnbaum· 3 shared A. Dimitrakakis· 2 shared C. Kaseke· 2 shared G. D. Gaiha· 2 shared H. Zeng· 2 shared J. Chen· 2 shared

Activity by Year

2019-2023 · peak 3/yr

Co-Author Collaboration Network

10 top collaborators · 30 mutual co-author links

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7 shared papersImmunology

D. K. Gifford

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Author profile →

10 papers

Recent·Most cited

Can a flower color ancestral polymorphism transcend speciation?

M. Sanchez-Cabrera, E. Narbona, M. Arista, P. L. Ortiz, F. J. Jimenez-Lopez, A. Fuller, B. Carter, J. Whittall

The paper investigates shared blue-orange petal color polymorphisms in two closely related species, suggesting an ancestral polymorphism that may have transcended speciation.

bioRxiv · Nov 14, 2023Evolutionary Biology

Machine learning model interpretations explain T cell receptor binding

B. Carter, J. Krog, M. E. Birnbaum, D. K. Gifford

The paper uses machine learning to predict TCR-pMHC binding and identifies sequence features associated with binding affinity.

bioRxiv · Aug 15, 2023 · PreprintImmunology

Epigenetic silencing by SMYD3 represses tumor intrinsic interferon response in HPV-negative squamous cell carcinoma of the head and neck.

N. Nigam, B. Bernard, S. Kim, K. Burkitt, D. Tsai, Y. Robbins, C. Sievers, C. T. Allen, R. L. Bennett, T. T. Tettey, B. Carter, R. Bao, L. Rinaldi, M. W. Lingen, H. Sater, , V. Saloura

This study identifies SMYD3 as an epigenetic regulator that suppresses the intrinsic interferon response in HPV-negative HNSCC, offering a potential strategy to enhance immunotherapy response.

bioRxiv · Nov 4, 2022 · PreprintCancer Biology

A pan-variant mRNA-LNP T cell vaccine protects HLA transgenic mice from mortality after infection with SARS-CoV-2 Beta

B. Carter, P. Huang, G. Liu, Y. Liang, P. J. C. Lin, B.-H. Peng, L. McKay, A. Dimitrakakis, J. Hsu, V. Tat, P. Saenkham-Huntsinger, J. Chen, C. Kaseke, G. D. Gaiha, Q. Xu, , D. K. Gifford

A T cell vaccine based on conserved epitopes protects HLA transgenic mice from SARS-CoV-2 Beta variant mortality without inducing neutralizing antibodies.

bioRxiv · Sep 23, 2022Immunology

Validity Assessment of Michigan's Proposed qPCR Threshold Value for Rapid Water-Quality Monitoring of E. coli Contamination

J. N. McNair, M. J. Lane, J. J. Hart, A. Porter, S. Briggs, B. Southwell, T. Sivy, D. C. Szlag, B. T. Scull, S. Pike, E. Dreelin, C. Vernier, B. Carter, J. Sharp, P. Nowlin, R. R. Rediske

The paper assesses the validity of Michigan's proposed qPCR threshold value for E. coli by comparing its performance with culture-based methods on test and training data.

bioRxiv · Jul 16, 2022Ecology

Preliminary Immunogenicity of a Pan-COVID-19 T Cell Vaccine in HLA-A*02:01 Mice

B. Carter, J. Chen, C. Kaseke, A. Dimitrakakis, G. D. Gaiha, Q. Xu, D. K. Gifford

This study tests a T cell vaccine in HLA-A*02:01 mice to assess its immunogenicity against SARS-CoV-2 variants.

bioRxiv · May 2, 2021 · PreprintImmunology

Machine learning optimization of peptides for presentation by class II MHCs

Z. Dai, B. D. Huisman, H. Zeng, B. Carter, S. Jain, M. E. Birnbaum, D. K. Gifford

The paper develops a machine learning method to optimize peptide binding to class II MHCs by modifying anchor residues, validated through a yeast display assay.

bioRxiv · Aug 18, 2020Immunology

Predicted Cellular Immunity Population Coverage Gaps for SARS-CoV-2 Subunit Vaccines and their Augmentation by Compact Peptide Sets

G. Liu, B. Carter, D. K. Gifford

The paper identifies gaps in SARS-CoV-2 subunit vaccine coverage for cellular immunity and proposes adding peptides to improve population coverage.

bioRxiv · Aug 4, 2020Immunology

Robust computational design and evaluation of peptide vaccines for cellular immunity with application to SARS-CoV-2

G. Liu, B. Carter, T. Bricken, S. Jain, M. Viard, M. Carrington, D. K. Gifford

The paper develops a machine learning method to design peptide vaccines for SARS-CoV-2, achieving high predicted coverage and robustness against epitope drift.

bioRxiv · May 16, 2020Immunology

Antibody Complementarity Determining Region Design Using High-Capacity Machine Learning

G. Liu, H. Zeng, J. Mueller, B. Carter, Z. Wang, J. Schilz, G. Horny, M. E. Birnbaum, S. Ewert, D. K. Gifford

This paper introduces a machine learning method to design human IgG antibodies with superior target affinity and specificity, using high-throughput data without requiring target structural information.

bioRxiv · Sep 3, 2019Immunology