Elsa Bernard is a Computational Oncology research fellow in Elli Papaemmanouil’s group. She obtained her Phd in Bioinformatics in 2016 from Mines ParisTech/Institut Curie (France). Elsa’s research interests broadly lie in the translation of computational genomics into personalized cancer medicine. She enjoys performing data-driven cancer research, that employs statistics and machine learning techniques, to translate genomic dependencies observed in patients into clinical support tools. Her main current focus is to better understand the genetic basis of myelodysplastic syndromes (MDS), genotype-phenotype relationships and determinants of outcomes and response to therapy. For more information, please check out Elsa’s website: https://elsab.github.io/