Welcome to the Huber group
The Huber group develops statistical and representation learning methods for modern biotechnologies, applies them to biological discovery, and translates them into reusable tools.
Our team studies biological systems by analysing new, cutting-edge data types and large systematic datasets: spatial and single-cell omics, high-throughput drug- and CRISPR-based perturbation assays, quantitative imaging. Projects range from biological discovery-driven to theoretical method development. We study fundamental biological model systems, as well as clinical samples for direct applications in biomedicine and precision oncology. We maintain an extensive network of collaborations. These include the Bioconductor project, the ELLIS Unit Heidelberg, the INTeRCePT 3.0 precision oncology project, the Molecular Medicine Partnership Unit (MMPU), and the ERC Synergy project DECODE.
Our interdisciplinary team brings together researchers from quantitative disciplines – such as physics, mathematics, statistics, computer science – and different fields of biology and medicine. We pursue three main aims:
- Develop and improve new data generating technologies—incl. single-cell and spatial omics, imaging-based phenotyping of high-throughput perturbation assays—by powering them with the best statistical methods. This includes inference – reasoning with uncertainty, making optimal decisions based on incomplete, noisy or overwhelming data – as well as data exploration and visualization: helping scientists make and discoveries from large, complex datasets that they could not grasp otherwise.
- Make biological discoveries in precision oncology, systems immunology. .
- Make statistical methods more widely usable, not only for experts, but for the range of natural scientists. This aim is embodied by our engagement in open source, open science and the Bioconductor project.