Vanessa D. Jönsson

PRISM : Peptide-specificity annotation of T-cell receptors with uncertainty quantification

PRISM improves TCR specificity prediction by addressing label scarcity and viral bias through synthetic data and uncertainty quantification, outperforming existing models on rare epitopes.

TRIOPS: A deep learning framework for prediction of T cell receptor-MHC binding specificity

TRIOPS predicts TCR-MHC restriction from amino acid sequences, achieving high AUC scores and generalizing to unseen alleles and HLA genotypes.

A rare HSC-derived megakaryocyte progenitor accumulates via enhanced survival and contributes to exacerbated thrombopoiesis upon aging

The paper identifies a rare HSC-derived megakaryocyte progenitor that accumulates with age, contributing to exaggerated thrombopoiesis and age-related platelet-mediated morbidities.

E2F1 induces a G0-G1 reentry transcriptional program without changing chromatin accessibility

The paper shows E2F1 induces cell-cycle reentry without changing chromatin accessibility by using pre-existing regulatory elements.

Pregnancy Reduces Il33+ Hybrid Progenitor Accumulation in the Aged Mammary Gland

This study shows pregnancy reduces Il33+ hybrid progenitor cells in aged mammary glands, improving lineage integrity and potentially lowering breast cancer risk.

Unraveling Neuronal Identities Using SIMS: A Deep Learning Label Transfer Tool for Single-Cell RNA Sequencing Analysis

SIMS is a deep learning tool for single-cell RNA sequencing classification that outperforms existing methods in accuracy and versatility across complex tissues and developmental stages.

An age-specific platelet differentiation path from hematopoietic stem cells contributes to exacerbated thrombosis

This paper identifies an age-specific platelet differentiation pathway from hematopoietic stem cells that contributes to thrombosis and platelet hyperreactivity in aging.