AI-driven genotype-phenotype modeling: a framework integrating multi-modal single-cell genomics and reverse vaccinology for de novo design of multi-epitope cancer vaccines.
- DOI
- 10.3389/fgene.2026.1909167
- Published
- 2026
- Container
- Frontiers in genetics
- Publisher
- Not recorded
- Open access
- yes
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Cite this work
BibTeX
@article{allodium:10.3389/fgene.2026.1909167,
title = {AI-driven genotype-phenotype modeling: a framework integrating multi-modal single-cell genomics and reverse vaccinology for de novo design of multi-epitope cancer vaccines.},
author = {Mallik M and Mollick SA},
year = {2026},
journal = {Frontiers in genetics},
doi = {10.3389/fgene.2026.1909167},
url = {https://doi.org/10.3389/fgene.2026.1909167}
}RIS
TY - JOUR TI - AI-driven genotype-phenotype modeling: a framework integrating multi-modal single-cell genomics and reverse vaccinology for de novo design of multi-epitope cancer vaccines. AU - Mallik M AU - Mollick SA PY - 2026 JO - Frontiers in genetics DO - 10.3389/fgene.2026.1909167 UR - https://doi.org/10.3389/fgene.2026.1909167 ER -
APA
M, M., & SA, M. (2026). AI-driven genotype-phenotype modeling: a framework integrating multi-modal single-cell genomics and reverse vaccinology for de novo design of multi-epitope cancer vaccines.. Frontiers in genetics. https://doi.org/10.3389/fgene.2026.1909167
Source records
- pubmed · retrieved 2026-11-10T10:48:24.136Z