We are a research group at Heidelberg University working at the interface of data science, machine learning and the life sciences. We develop computational tools and statistical methods that are required to translate large-scale molecular data sets (‘omics data’) into biological insights and novel discoveries.
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| MOFA | MEFISTO |
| Multi-omics factor analysis | Integrating temporal and spatial omics data |
| Webpage | Webpage |
| Publications: general, multi-group | Publication |
| Bioconductor: MOFA2 | Bioconductor: MOFA2 |
| PyPI: mofapy2 | PyPI: mofapy2 |
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| FISHFactor | |
| Modelling spatial transcriptomic data with subcellular resolution |
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| GitHub page | |
| Publication |