Causal and mechanistic modelling strategies, which aim to infer cause–effect relationships, provide insights into cellular responses to perturbations. The authors review computational approaches that harness machine learning and single-cell data to advance our understanding of cellular heterogeneity and causal mechanisms in biological systems.