The advances in high-throughput technologies are providing unprecedented opportunities to better understand human diseases. Recent years have in this context witnessed the accumulation of omics approaches and datasets. Biomedicine is further transitioning from multiomics to multimodal datasets: data are not only available at the molecular omics level, as we now have access to signals and images, but also to various datasets related to disease phenotypes, health databases, or drug chemical similarities. The bottleneck now lies in the analysis and integration of these complex, large-scale and heterogeneous datasets. The Systems Biomedicine team bridges the gaps by harnessing digital expertise and developing novel computational approaches.
- Biostatistics
- Artificial Intelligence
- Multi-scale analysis and modelling
- Machine learning
- Bioinformatics & Biomedical
- Biological network inference and analysis
- genetic diseases
- Data Integration
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