We design experiments in molecular cancer biology to model the process of cancer initiation (oncogenesis). Our aim is to trace DNA and RNA trajectories at cellular resolution and quantify necessary and sufficient early conditions for cancer to occur. We closely collaborate with experimental biologists on both designing and performing the experiments, throughtout the data generation process.
1. Cancer biology: We design and/or apply computational methods to analyse and predict (i) mutational (DNA) interactions, and (ii) transcriptional (RNA) trajectories, during cancer initiation
2. Population biology: We develop causal (non-)parametric stastitical and machine learning techniques for applications to large-scale biomedical data, such as scRNA-seq and the UK Biobank.
1. Causality in Biomedicine: Aimed at biologists, computer scientists and more broadly researchers from quantitative backgrounds. Two main topics of (i) Causal Effect Estimation and (ii) Causal Discovery are covered, together with biomedical applications.
2. PhD projects (contact)
3. MSc projects (contact)
4. BSc summer projects (contact)
Ava Khamseh, Group Leader/Lecturer in Biomedical AI