Computational Biology

We develop computational approaches to find clinically relevant mutations in cancer cells.

Group Leader

What we do

Personalised medicine is changing the way that cancer is treated. New technology is generating huge amounts of data from individual children’s tumours, and this data holds the key to understanding and treating their cancer. Our group aims to improve outcomes for children with cancer by getting the most out of that data.

We develop computational approaches (algorithms) that can identify and prioritise clinically relevant mutations in a child’s cancer cells. If we can understand what is driving those cells to grow, and/or how they overcome conventional therapies, we can use that information to help design the treatment strategies most likely to work.

Personalised medicine is increasingly becoming a data science, and so we also develop methods to integrate the data we generate with data in public access databases. This maximises its impact — the data doesn’t just benefit individual cancer patients today; it also contributes to our overall understanding of cancer. This sort of collaborative multidisciplinary research answers bigger, further-reaching questions.

Our goals are to:

  • Improve outcomes for children with high-risk cancer, through developing methods which improve the quality of precision medicine.

  • Develop innovative methods to characterise the molecular profile of each tumour, and use these to analyse large-scale public data sets.

  • Develop methods to investigate the impact of non-coding mutations on cancer.

  • Understand the increasing role of genetic factors underlying cancer predisposition.

Research projects

Translational bioinformatics: Zero Childhood Cancer

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Contact: A/Prof Mark

Our group provides the bioinformatic and genomics expertise that underly the molecular profiling used in the Zero Childhood Cancer (ZERO) national clinical trial. We analyse the vast amounts of molecular data (WGS, RNA-Seq and methylation) obtained from each child’s tumour sample and develop methods to identify and prioritise mutations, so those that are most medically relevant and clinically actionable get focused on. We mine the data for this information in real-time and feed our results back to the ZERO variant curation team and Molecular Tumour Board. This ultimately helps treating oncologists decide on the treatment strategy with the best possible chance of success for each child on the clinical trial.

We also develop methods to integrate the data we generate with data in public access databases, so we are adding our knowledge to a growing pool.

Probing the dark matter of the high-risk paediatric cancer genome

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Contact: A/Prof Mark Cowley,

The human genome is vast, and only 2% of it encodes genes. One of the great challenges in genomics is to understand what genetic variation in the other 98%, the ‘dark matter’, does, and how it contributes to cancer.

There are a number of obvious places to begin looking. We will initially investigate the role of non-coding genetic variation on the sequences which are responsible for controlling gene splicing, gene regulation, and patterns of retrotransposon activation. By combining large amounts of matched WGS and RNA-Seq data from patients, we will start to systematically tackle the non-coding genome and begin to understand how this contributes to paediatric cancer. By investigating these noncoding mutations, we hope to gain a better understanding of high-risk childhood cancer, and potentially identify new drug targets.

This project is supported by a Cancer Australia Grant (2019–21).

Redefining germline paediatric cancer risk

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Contact: Dr Mark

Why do children get cancer? We believe that many children who develop cancer were born at a high risk of developing the disease. However, we can currently find a genetic cause in only around 10% of childhood cancers. Our research aims to improve this rate by improving our understanding of how a child’s DNA affects their chances of developing cancer.

We are doing this by:

  • Investigating new ways in which the genome affects cancer risk, by looking at the dark matter of the genome.

  • Examining how genes and the environment work together to control a child’s chance of developing cancer.

  • Searching for pre-cancerous changes in healthy children.

We hope our findings will result in tools to help predict childhood cancer risk, as well as tools which can improve outcomes through earlier diagnosis in high-risk children, and better inform the families of children with cancer.


Senior Bioinformatics Research Officers

Dr Maely Gauthier

Dr Mark Pinese

Senior Bioinformatics Engineer

Dr Marie Wong-Erasmus

Honours Student

Patricia Sullivan

PHD Student

Chelsea Mayoh

Undergraduate Research Intern

Rachel Bowen-James

Get in touch

Do you have a question about our work? For any enquiries please don’t hesitate to contact us.

Your donation will fund research that will save young lives!