MAST90106/90107 Data Science Project of the University of Melbourne

Team Members:

• Zexi Liu - 813212 - [email protected]
• Haoze Xia - 1131343 - [email protected]
• Atefeh Zamani - 1129712 - [email protected]
• Ni Zhang - 1081143 - [email protected]
• Tianyu Zhou - 1199306 - [email protected]

Academic Supervisor: Dr Jiadong Mao - [email protected]

Subject Coordinator: Professor Michael Kirley - [email protected]

Epigenetic Classifier for Twin Zygosity

Epigenetic modifications alter DNA expression without changing the DNA sequence. While monozygotic twins have the same DNA sequence, they could have different epigenetic modifications. Twins have been suggested to have unique epigenetic features. This project hypothesizes that the zygosity of twins (monzogytoic, dizygotic) can be accurately predicted by epigenetic markers, and aims to develop an epigenetic classifier for twin zygosity using high-dimensional DNA methylation data measured by the microarray chip and machine-learning techniques.

A research report easily modified to an article for a scientific journal.

Host Organisation Name: Twins Research Centre of Epidemiology and Biostatistics UoM

Industry Contact:

• Dr Sue Malta (Senior Manager and Researcher) - [email protected]
• Dr Shuai Li - [email protected]

Industry Address: Level 3, 207 Bouverie Street, Carlton South, VIC 3054, Australia

• Centre for Epidemiology and Biostatistics of UoM: https://mspgh.unimelb.edu.au/centres-institutes/centre-for-epidemiology-and-biostatistics
• Twins Research Australia of UoM: https://mspgh.unimelb.edu.au/research-groups/centre-for-epidemiology-and-biostatistics-research/australian-twin-registry
• Twins Research Australia official website: https://www.twins.org.au/