Strategic Research

Genome Data Science (aGENDAS)

In order to address outstanding questions in biology and medicine, researchers need to discover meaningful and robust patterns from data. In the aGENDAS group, we strive to elucidate the links between mutational processes, natural selection, gene function and phenotype by means of statistical genome analyses. In particular, we use cutting-edge computational techniques and machine learning methodologies for exploring massive genomic data sets.

We aim to answer important biological questions by insightful analysis of data originating from human cancers (somatic mutations, chromosomal alterations, transcriptomes), human populations (germline variants), metagenomics (including human microbiomes) and also fully sequenced microbial genomes.




Bioinformatics expertise:

Group Leader:

Fran Supek