We are investigating the mechanisms by which new genes originate with a special emphasis on genes originated de novo from previously non-coding genomic regions. The research is strongly based on the analysis of transcriptomics and translatomics (RiboSeq) data from related species and individuals. We are examining different model systems, including human cell lines and yeast isolates. Additionally, we are taking advantage of long read transcriptomics technologies to learn about the changes in gene structure and expression across evolutionary time.

We are investigating how the accumulation of mutations during cancer progression, as well as the translation of non-canonical ORFs in cancer-specific transcripts, can result in the production of neoantigens with the capacity to trigger an immune response against the cancer cells. We are also developing machine learning methods to improve the prediction of the response to immunotherapy using extensive whole exome sequencing and transcriptomics data.