AI Methods for Biological Discovery
AI methods that turn biological data, knowledge and experimental constraints into hypotheses, interpretable rules, trajectories, dynamical models, virtual systems and defensible predictions
FROM BIOLOGICAL DATA TO SCIENTIFIC OBJECTS – July 2026
Hypotheses | Interpretable rules | Cellular trajectories | Dynamical models | Calibrated simulators | Verified causal worlds | ML-ready data | Prediction pipelines
Explore the van der Schaar Lab’s portfolio of AI methods for biological discovery below.
This catalogue is organised around the scientific object you may need next – from hypotheses and interpretable rules to cellular trajectories, dynamical models, calibrated simulators, verified causal worlds and defensible predictive pipelines.
If you have a question about one of the methods, are interested in applying the research to a biological or medical problem, or would like to discuss a potential collaboration, please complete our enquiry form.
