Judith Abecassis is a graduate student from the Ecole Normale Supérieure currently at Institut Curie and Mines ParisTech under the supervision of Jean-Philippe Vert and Fabien Reyal. She first studied Biology for two years, and after a competitive exam, was accepted into the Ecole Normale Supérieure de Paris to complete her Bachelors in Biology. She then spent a year in the Masters program in Genetics, Genomics and Evolution. She chose to major in Machine Learning and Computer Vision to be able to perform better bioinformatics analyses on large datasets, which has always been her main research interest. Her research focuses in enrichments in the analysis of the mutational landscape in cancer. She is working on three main projects. The first one concerns the reconstruction of tumoral subclonal heterogeneity from mutation and alteration data obtained by high-throughput sequencing. A first objective will be to evaluate the impact of tumor heterogeneity in a cohort of breast cancer patients resistant to treatment. The other two projects are related to this one. One concerns the combination of several mutation callers to improve accuracy of existing algorithms to call mutations from high-throughput sequencing data. Another one concerns the impact of the mutational landscape in relapse and resistance to chemotherapy.