Developing predictive models for precision medicine
At IBM Research – Zurich, we develop novel approaches to analyze different molecular levels of high-throughput data. From single-cell to cell population-averaged data (proteomics, transcriptomics), we aim to integrate multiple layers of genome-scale information. This, in combination with clinical information and prior knowledge through literature mining, enables us to understand molecular mechanisms and explore applications to personalised medicine.
Our main research projects include, but not are limited to, studying cell-to-cell heterogeneity, integrative multi-omics analysis, dynamic network inference and robust biomarker discovery, most of which are applied in the case of cancer.
We gratefully acknowledge our numerous collaborations with university hospitals, research institutes and universities that work alongside our team in many of our projects.
Identifying the sources of cell heterogeneity is crucial to developing effective disease management strategies.