What we do

We develop concepts and algorithmic tools for the analysis of large-scale biological and clinical data. We participate in many genome-wide association studies (GWAS) for human traits and have a particular interest in the integration of genotypic and complex phenotypic datasets (such as gene expression or metabolomics). A key approach is the reduction of complexity through modular and network analysis. A complementary direction of our research pertains to relatively small genetic networks, whose components are well known.

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Main publications 2020

  • Tomasoni M et al.
    MONET: a toolbox integrating top-performing methods for network modularization
    Bioinformatics, 10.1093/bioinformatics/btaa236
  • Cohen R et al.
    Mechanical forces drive ordered patterning of hair cells in the mammalian inner ear
    Nature Communications, 10.1038/s41467-020-18894-8
  • de Las Fuentes L et al.
    Gene-educational attainment interactions in a multi-ancestry genome-wide meta-analysis identify novel blood pressure loci
    Molecular Psychiatry, 10.1038/s41380-020-0719-3

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