The space of evolutionary trees in infectious disease epidemiology
- Research Opportunity
- Masters by Research, Honours students
- Department / Centre
- Microbiology and Immunology
- Location
- Doherty Institute
Primary Supervisor | Number | Webpage | |
---|---|---|---|
Dr Sebastian Duchene | sebastian.duchene@unimelb.edu.au | 8344 3971 | Personal web page |
Co-supervisor | Number | Webpage | |
---|---|---|---|
Dr Mark Davies | mark.davies1@unimelb.edu.au | (03) 9035 6519 | Personal web page |
Summary This project has three main aims; (i) estimating evolutionary parameters for a range of pathogens, such as HIV, influenza, and dengue, (ii) using these parameters to simulate evolutionary trees under different epidemiological models, and (ii) applying machine learning techniques to identify whether epidemiological processes lead to a predictable patterns of evolutionary trees.
Project Details
Infectious disease epidemiology relies on mathematical models that describe epidemiological dynamics. These models typically consider the rate at which individuals are infected and recover from an infection. Because many infectious microbes, such as viruses and bacteria, evolve orders of magnitude faster than their hosts, their genomes have a signature of the transmission process. This project will pinpoint the key differences between evolutionary trees generated under different epidemiological processes. This project has three main aims;
- estimating evolutionary parameters for a range of pathogens, such as HIV, influenza, and dengue,
- using these parameters to simulate evolutionary trees under different epidemiological models, and
- applying machine learning techniques to identify whether epidemiological processes lead to a predictable patterns of evolutionary trees. The outcome will be a framework to classify evolutionary trees from genome surveillance studies, which will contribute to current efforts to couple genomics and epidemiology.
Faculty Research Themes
School Research Themes
Research Opportunities
Masters by Research, Honours students
Students who are interested in joining this project will need to consider their elegibility as well as other requirements before contacting the supervisor of this research
Key Contact
For further information about this research, please contact a supervisor.
Department / Centre
Research Node
Doherty InstituteMDHS Research library
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