Reconstruct trans-regulatory networks using multi-omics profiling and data integration

Summary

A major initiative in our group is to integrate trans-omics datasets generated by a state‐of‐the‐art mass spectrometer (MS) and next-generation sequencer (NGS) from various cell systems. We have now profiled various stem/progenitor cell differentiation processes using a combination of MS and NGS and have generated large-scale trans-omics datasets in these cell systems (see https://doi.org/10.1016/j.cels.2019.03.012. These data provide exciting research directions where we hypothesize that data integration across multiple omic layers is the key to a comprehensive understanding of the underlying biological systems. 

A complimentary scholarship for this project may be available through a competitive process. To find out more, refer to the Faculty of Science Postgraduate Research Excellence Award and contact Dr Pengyi Yang directly.

Supervisor(s)

Dr Pengyi Yang

Research Location

School of Mathematics and Statistics

Program Type

PHD

Synopsis

The aim of this PhD project is to develop computational methods for integrating and making sense of multi-layered omic datasets. Specifically, you will be developing and applying unsupervised, semi-supervised and supervised machine learning techniques and general data analytics for integrating and making sense trans-omics data that capturing the dynamics of stem and progenitor cell differentiation. Programming skill is essential for this project. Knowledge discovered from this project will translate into exciting biological findings and shed light on development, regeneration, and treatment for complex diseases and aging.

Additional Information

A complimentary scholarship for this project may be available through a competitive process. To find out more, refer to the Faculty of Science Postgraduate Research Excellence Award and contact Dr Pengyi Yang directly. 

HDR Inherent Requirements  

In addition to the academic requirements set out in the Science Postgraduate Handbook, you may be required to satisfy a number of inherent requirements to complete this degree. Example of inherent requirement may include:   

  • Confidential disclosure and registration of a disability that may hinder your performance in your degree;
  • Confidential disclosure of a pre-existing or current medical condition that may hinder your performance in your degree (e.g. heart disease, pace-maker, significant immune suppression, diabetes, vertigo, etc.);
  • Ability to perform independently and/or with minimal supervision;  
  • Ability to undertake certain physical tasks (e.g. heavy lifting);  
  • Ability to undertake observatory, sensory and communication tasks;  
  • Ability to spend time at remote sites (e.g. One Tree Island, Narrabri and Camden);  
  • Ability to work in confined spaces or at heights;  
  • Ability to operate heavy machinery (e.g. farming equipment);  
  • Hold or acquire an Australian driver’s licence;  
  • Hold a current scuba diving license;  
  • Hold a current Working with Children Check;  
  • Meet initial and ongoing immunisation requirements (e.g. Q-Fever, Vaccinia virus, Hepatitis, etc.)   

You must consult with your nominated supervisor regarding any identified inherent requirements before completing your application.

Want to find out more?

Contact us to find out what’s involved in applying for a PhD. Domestic students and International students

Contact Research Expert to find out more about participating in this opportunity.

Browse for other opportunities within the School of Mathematics and Statistics .

Keywords

cell regulatory networks, computational models, omics data

Opportunity ID

The opportunity ID for this research opportunity is: 2713

Other opportunities with Dr Pengyi Yang