Elsa Bernard

This study uses optical genome mapping to analyze C9orf72 repeat expansion instability in blood from ALS and FTD patients, finding age-dependent differences in repeat size dynamics between conditions.

SHERLOC is a deep learning model for survival analysis using longitudinal ctDNA data, showing improved discrimination and calibration over existing methods in non-small-cell lung cancer.

This study shows that DNMT3A R882H mutant HSCs resist inflammatory stress through delayed p53 activation, leading to clonal expansion and increased AML risk.

The paper examines TP53 allelic states in MDS patients, finding that bi-allelic targeting is linked to worse outcomes, while mono-allelic targeting does not differ from wild-type patients.

The paper shows oncologic therapy increases clonal hematopoiesis with DDR mutations, which predicts risk of therapy-related myeloid neoplasms.

This paper introduces kernel multitask regression to predict compound toxicity on cell lines using chemical and genetic data, achieving strong performance on a benchmark challenge.