3 papers
q-bio.GN2025
Leveraging genomic deep learning models for the prediction of non-coding variant effects
Pooja Kathail, Ayesha Bajwa, Nilah M. Ioannidis
Characterizing non-coding variant function remains an important challenge in human genetics. Genomic deep learning models have emerged as a promising approach to enable in silico p…
q-bio.QM2025
Generation of structure-guided pMHC-I libraries using Diffusion Models
Sergio Mares, Ariel Espinoza Weinberger, Nilah M. Ioannidis
Personalized vaccines and T-cell immunotherapies depend critically on identifying peptide-MHC class I (pMHC-I) interactions capable of eliciting potent immune responses. However, c…
q-bio.QM2025
Continued domain-specific pre-training of protein language models for pMHC-I binding prediction
Sergio E. Mares, Ariel Espinoza Weinberger, Nilah M. Ioannidis
Predicting peptide--major histocompatibility complex I (pMHC-I) binding affinity remains challenging due to extreme allelic diversity (30,000 HLA alleles), severe data scarci…