
Gaining a full picture of cell differentiation using experiments-in-the-loop
Our lab integrates advanced computational and experimental techniques to establish a dynamic experiment-in-the-loop approach for studying cell differentiation. We create and leverage computational tools to model the interplay between microenvironmental cues and chromatin dynamics during differentiation. These predictions are then tested in vivo using untargeted spatial, transcriptomic, and chromatin profiling techniques. After several months, we gather the in vivo profiles to validate the predictions, feeding the results back into the computational models to further refine and enhance their accuracy.
This iterative process creates a continuous feedback loop between prediction and experimentation, enabling precise insights into cellular differentiation. Although our approach can be broadly applied, our current focus is on lung and liver macrophages — systems that allow for effective perturbation and provide robust models of true in vivo differentiation.
Areas of Expertise
- Modelling of spatial and single-cell omics
- Single-cell perturbation screens in vivo
- Probabilistic modelling
- Experiment-in-the-loop
Technology Transfer Potential
- Semi-automated identification of key regulators underlying immune cell state
- Predicting effects of a perturbation
Selected publications
- Saelens W., et al. ChromatinHD connects single-cell DNA accessibility and conformation to gene expression through scale-adaptive machine learning, bioRxiv, 2024. Visit ➚
- Liu W., Saelens W. et al. Dissecting reprogramming heterogeneity at single-cell resolution using scTF-seq, bioRxiv, 2024. Visit ➚
- Guilliams M. et al. Spatial proteogenomics reveals distinct and evolutionarily conserved hepatic macrophage niches, Cell, 2022. Visit ➚
- Browaeys R., Saelens W., et al. NicheNet: modeling intercellular communication by linking ligands to target genes, Nature Methods, 2020. Visit ➚
- Saelens W., et al. A comparison of single-cell trajectory inference methods, Nature Biotechnology, 2019. Visit ➚
Bibliography
- Full bibliography Visit ➚
