In the GenomeDataLab, we use statistical genomics and machine learning to study quality control (QC) mechanisms that protect the integrity of information stored in the cell: its genome and the transcriptome.

We perform large-scale bioinformatic studies of multi-omic data from human tumors (somatic mutations and transcriptomes), human populations (germline variation) and metagenomes (incl. human microbiomes).

We study mechanisms of maintaining genome stability in human cells via statistical analyses of mutation patterns in cancer, which often result from deficient DNA repair [ 1 ]. Next, we are interested in how mRNA synthesis and turnover pathways shape genomes and transcriptomes in health and disease [ 2 ]. Finally, we combine experimental work and genomics to scan cancer genomes for genetic interactions to predict tumor evolution and identify novel synthetic lethalities [ 3 ]. More generally, we study novel applications of machine learning methods to infer gene function from genomics [ 4 ].

read more about our research interests >>>

Some recent publications from the GenomeDataLab:

Meet the GenomeDataLab team:

We gratefully acknowledge our funders:

European Research Council ERC Starting Grant #757700 HYPER-INSIGHT "Insight into genome maintenance and cancer vulnerabilities provided by an extreme burden of somatic mutations "

Fran Supek is an EMBO Young Investigator.

EU H2020 DECIDER "Clinical Decision via Integrating Multiple Data Levels to Overcome Chemotherapy Resistance in High-Grade Serous Ovarian Cancer"

PI is tenured by the ICREA Research Professor program.

We are further funded by the "Severo Ochoa" centres of excellence program (to IRB), the Spanish Ministry of Science, Innovation and Universities (REPAIRSCAPE), the Catalan Science Agency, and the Croatian Science foundation. More information on projects >>>

Some collaborations of the GenomeDataLab:

  • Proton and alpha radiation-induced mutational profiles in human cells

  • TM Delhomme, M Buonanno, V Grilj, J Biayna, F Supek (2022)
    coming soon in bioRxiv

We are a part of the Institute for Research in Biomedicine (IRB Barcelona), a member of the Barcelona Institute of Science and Technology:

"Prediction is very difficult, especially about the future." -- Niels Bohr.