Computational approaches for elucidating mutational processes that generate genetic diversity within populations and across species, with the goal of understanding mechanisms of mutagenesis and DNA repair.
Fran is also interested in developing statistical frameworks for detecting genomic signatures of selection, which are often challenging to distinguish from the background DNA sequence variability that results from accumulated mutations. Such novel methodologies provide opportunities to gain insight into evolution of genomes, by revealing details of the interplay between mutation and selection.
The biological questions Fran addressed include learning about evolution of gene function and regulation, in particular related to mechanisms underlying stress resistance and disease. In addition, Fran is interested in distributions of genetic variants in the human germline and soma, which reveal how DNA repair is organized across chromatin.
Hosted by Julian Ceron – Modeling human diseases in C. elegans Group
Fran leads the Genome Data Science laboratory at the IRB Barcelona, which specializes in large-scale statistical analyses of genomic, transcriptomic and epigenomic data. Fran obtained his PhD in Molecular biology in 2010 from the University of Zagreb, while working as an early-stage researcher at the RBI (Croatia) on machine learning in comparative genomics. This was followed by a postdoctoral stay at the Centre for Genomic Regulation (as a Marie Curie fellow), studying cancer genome evolution. In 2017 he started his lab as a Ramón y Cajal fellow. Fran is the PI of the ERC Starting Grant HYPER-INSIGHT, an EMBO Young Investigator, and an ICREA tenured professor. He authored 50 research papers (including in Nature, Cell and Nature Genetics), 3 invited review articles and 2 book chapters, cited >9000 times.