Pioneers in the emerging imaging omics approach, where imaging morphological data and spatial transcriptomics and proteomics are integrated to study in vivo biological processes

Cancer first starts as single cancer cells and evolves within an ecosystem of multiple cell types in a tissue.

Understandings of the heterogeneity of cancer cells in their cellular ecosystem will allow for early diagnosis, accurate prognosis and targeted treatment of cancer.

The Genomics and Machine Learning Lab is applying imaging genomics to study cancer in every single cells and within their spatial tissue context.

We aim to address long-standing questions on how individual cell types are different and how do these multiple cell types coexist and develop as an ecosystem within a diseased tissue.

Our goal is to find cure for cancer one cell at a time.


Spa cell

Group leader

Dr Quan Nguyen

Dr Quan Nguyen

Group Leader, Genomics and Machine Learning

  +61 7 334 62394
  UQ Researcher Profile

We aim to improve diagnosis and disease management by advancing understandings of cancer and immune cells at single cell level and within tissue morphological context. Our mission is to cure disease one cell at a time within an ecosystem of millions of cells.

Our daily research strives for creativity and innovations. We like new challenges and are keen to explore areas outside our comfort zones. Each member in the group is a leader and all members are supporting each other. We respect diversity, equity and integrity.

We have developed innovative machine learning approaches to find cancer cells and predict their progression within histopathological images.

We are always open to research collaborations and looking for complementary expertise to our spatial omics capability.

Our research is supported by Australian Research Council, National Health and Medical Research Council, Genome Innovation Hub (UQ), Metro North Hospital and Health Service, Brisbane Diamantina Health Partners, RBWH and RBWH Foundation, The Australian Skin and Skin Cancer Research Centre (ASSC), VinGroup Innovation Fund

We collaborate closely with cancer and neuroscience researchers. Collaborative projects often require sample recruitment, data generation, analysis, interpretation and validation. Our collaborations results in shared senior/first-authored publications and co-applications for funding.