• Paediatric Precision Medicine

Computational Biology

Project Overview

The Computational Biology Program will integrate and interpret ‘omic (i.e. genomic sequence, protein, metabolite, and microbiome information), biological, and clinical data to accelerate the translation of research findings into a clinical environment and improve patients’ access to new clinical trials, as well as, inform new programs for prevention and earlier diagnosis of disease in the community. This will ultimately lead to more effective treatment strategies for sick children, and their families so that they live longer and better, and reduce the burden on the healthcare system. The predictive models insights will also undoubtedly have utility beyond paediatrics such as adult cancer and other rare disease disciplines. The outcome from this investment will be that children and families in New South Wales will experience world class healthcare improving access to the right treatment at the right time.

Collaborations

  • Children’s Cancer Institute (Australia)
  • Kids Cancer Centre Sydney Children’s Hospital, Randwick, Sydney Children’s Hospitals Network (Australia)
  • Zero Childhood Cancer national and international partners network (8 hospitals, 20 research institutes), including all three NSW Paediatric oncology centres, Peter MacCallum Cancer Centre, Murdoch Children’s Research Institute, Garvan Institute of Medical Research, ProCan Proteomics, Children’s Medical Research Institute (Australia)
  • Children’s Hospital Westmead, Sydney Children’s Hospitals Network (Australia)
  • Children’s Medical Research Institute (Australia)
  • University of NSW (Australia)
  • Sydney University (Australia)
  • Children’s Hospital of Philadelphia (USA)
  • Australian Bioinformatics Data Commons (Australia)
  • Sick Kids, Toronto (Canada)
  • Hartwig Medical Foundation (Australia, Netherlands)
Summary

Precision medicine utilises large data sets that combine omics with clinical information and health outcomes to optimize disease diagnosis, treatment and prevention specific to each patient.

Lead Investigators

  • Mark_Cowley@2x

    Associate Professor Mark Cowley

    Group Leader, Computational Biology Group, Children’s Cancer Institute
  • Vanessa_Tyrell@2x

    Vanessa (Ness) Tyrrell

    Co-Head, Personalised Medicine Theme, Children’s Cancer Institute

Team

  • Dr Marie Wong-Erasmus

    Precision Medicine Informatics Manager, Children’s Cancer Institute (Australia)
  • Dr Mark Pinese

    Snr Bioinformatics Research Officer, Children’s Cancer Institute (Australia)
  • Dr Irene Chen

    Snr Bioinformatics Research Officer, Children’s Cancer Institute (Australia)
  • Mustafa Syed

    Senrio Bioinformatics Engineer, Children’s Cancer Institute (Australia)
  • Sabrina Yan

    Bioinformatics Research Assistant, Children’s Cancer Institute (Australia)
  • Louise Cui

    Bioinformatics Research Assistant, Children’s Cancer Institute (Australia)
  • Sam El-Kamand

    Bioinformatics Research Assistant, Children’s Cancer Institute (Australia)
  • Chelsea Mayoh

    PhD student, Children’s Cancer Institute (Australia)
  • Patricia Sullivan

    PhD student, Children’s Cancer Institute (Australia)
  • Rachel Bowen-Jones

    Honours student, Children’s Cancer Institute (Australia)