T cell receptor cross-reactivity prediction improved by a comprehensive mutational scan database

2025/07/25 by Amitava Banerjee, David Pattinson, David J. Pattinson +6 · 2 voices · 1 citation
Biochemistry, Genetics and Molecular Biology · Immunology and Microbiology · Medicine · #Monoclonal and Polyclonal Antibodies Research #T-cell and B-cell Immunology #vaccines and immunoinformatics approaches

paper · doi:10.1016/j.cels.2025.101345

openalex publication_date 2025/07/25 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/01

Citations

• UCSF ChimeraX: Tools for structure building and analysis
• Three-dimensional hydrogen-bond geometry and probability information from a crystal survey
• 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
• Can we predict T cell specificity with digital biology and machine learning?
• Predicting adaptive immune receptor specificities by machine learning is a data generation problem

Cited by

• AI Developments for T and B Cell Receptor Modeling and Therapeutic Design

Discussions

• First postdoc paper with @hannahvmeyer.bsky.social on #TCR cross-reactivity database & modeling out now in Cell Systems: doi.org/10.1016/j.ce... BATCAVE database + Paper codes: github.com/meyer-lab-c [bsky, 9 points, 0 comments]
• 🦇 Really cool work from our good friend and brilliant former colleague @hannahvmeyer.bsky.social in @cp-cellsystems.bsky.social I always get questions on TCR cross-reactivity predicted from peptide [bsky, 3 points, 1 comments]