The broad aim of my Master’s research project is to identify susceptive genes of Congenital Heart Defects (CHDs) by exploring high-throughput DNA methylation data. The research theme is initiated from a multi-disciplinary study where we investigated the exact cause of most CHDs by collecting blood samples at Kind Edward Memorial Hospital for Women, WA. This project is part of a collaboration between Edith Cowan University (ECU), Curtin University, the University of Western Australia (UWA), and Department of Health (DoH).
We developed a pipeline to analyse a small-sample-sized high-dimensional methylation data set to identify biomarkers for CHDs. A total of 48 clinically collected genome-wide DNA methylation profiles were used to investigate the usefulness of DNA methylation as biomarkers in diagnosing and predicting children with CHDs. We conducted primary pre-processing on the dataset, then applied a data mining approach (random forest classifiers) on the resultant dataset. Our investigation highlighted that aberrant DNA methylation may play a significant role in the pathogenesis and occurrence of CHDs.
Biography
I am a software engineer and biostatistician with experience of working in both Higher Education and Health Departments. I am also a researcher. My research focuses on the application of statistics in population studies with expertise in the use of machine learning in high-dimensional biology.
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Past Research employment history
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Past Teaching