LncRNAs and Data Analytics

Wilson Wong

BSc (Hons), PhD
Wilson is a researcher trained in microRNA and lncRNA biology, molecular biology and high-dimension data analytics. He is currently focusing on understanding the role of lncRNA variants that he identified to be important in regulating human islet beta-cell survival. Wilson leads this area of lnc-RNA biology and co-leads other projects related to high dimensional data analysis. Wilson received his PhD from the University of Sydney for his work in islet microRNAs and diabetes. He was supported through a University postgraduate scholarship and a PhD top-up award from JDRF Australia. He then received training in data analyses through collaborators in Hong Kong (Prof. Ronald Ma) and Denmark (Prof. Louise Dalgaard) following his PhD. Wilson joined back with the Diabetes and Islet Biology group to continue his research interests through a JDRF Australia and the Helmsley Trust innovative DREAM Nano grant (to A/Prof. Hardikar). Wilson is also the recipient of the 2020 Australian Diabetes Society Lindsey Baudinet Rising Star Award, which offers him the opportunity to continue on important leads in understanding the role of islet-enriched lncRNAs in post-isolation islet cell survival. At WSU, Wilson leads lncRNA research mainly with reference to islet function. He also works closely with Dr. Mugdha Joglekar and A/Prof Hardikar on projects involving microRNA-lncRNA interactions in islet biology. Wilson works within the Diabetes and Islet Biology Group at Western Sydney University and is affiliated with the Translational Health Research Institute (THRI), Western Sydney University. He also collaborates with clinician-researchers and academics within the Diabetes, Obesity and Metabolism Translational Research Unit.
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Our research -

What do we do?
We are mainly interested in understanding how long-non-coding (lnc)RNAs regulate human islet beta-cell survival. I am also interested in understanding how other ncRNAs, such as microRNAs, and lncRNAs interact with each other in regulating the expression of pro-endocrine genes within human islets. I work closely with A/Prof. Hardikar and Dr. Mugdha Joglekar on understanding how data-driven approaches could help in identifying biomarkers of future disease.
How do we do?
Scientific methodologies include unprejudiced discovery analyses followed by validation and prediction in a larger number of clinical/biological samples. We use machine-learning algorithms, similar to how social media or Netflix would suggest you your next favourite movie! Through A/Prof. Hardikar's collaborative links within the academia and the industry, we work with several biostatisticians and data scientists for independent validation of our analyses using separate workflows in R- /Python.
Who may benefit?
Using machine-learning workflows and data analytical tools on high-dimensional datasets that we have generated, and those that we can access through public datasets, we are uniquely placed in identifying ncRNA regulators of islet hormone production. Through the Diabetes and Islet Biology group, we have the capacity to validate these ncRNAs and test the relevance of these mechanisms in human disease. Ultimately, our work may help advance knowledge in how to better manage and/or treat type 1 diabetes.

Selected current projects -

  • Identifying the role of MALAT1 lncRNA variants in islet cell survival and beta-cell function (through support from my Australian Diabetes Society Lindsey Baudinet Rising Star Award)
  • The DREAM-Nano Study. Developing a Robust and Efficient Analytical Method for Diabetes Progression using Nanotechnology (with Prof. Hardikar and collaborators)
  • Several data-driven projects in identifying biomarkers associated with and predictive of future disease (with Prof. Hardikar, Dr. Mugdha Joglekar, Prof. Louise Dalgaard, Prof. Stephen Gitelman, Dr. Milan Piya, Prof. Ronald Ma and others)