Bioinformatics
Comparing the importance of genes across species - also offered as MBiomedSc
Supervisors: Slavé Petrovski and David Balding
Project Site: Department of Medicine RMH, Kenneth Myer Bldg
Contact: Slave Petrovski E: slavep@unimelb.edu.au
Project description: This is a population genetics project that will leverage two collections of information. Much excitement has emerged from our recent ability to quantify with good resolution the human-specific constraint (also called “intolerance”) of human genes. We will use a collection of human gene intolerance metrics and compare them to traditional metrics of phylogenetic conservation. The goal of this study is to use standing human genetic variation from large population studies to identify genes in which the selective pressures among modern humans differs from that estimated from cross-species comparisons (considering vertebrate, mammalian and primate species). That would indicate a recent change in the role of selection that could highlight genes of functional importance in human development and disease. This project has the potential to gain insight into human adaptations, but also may facilitate predictions of which human disease genes are more likely to be amenable to animal modelling of human disease.
Skill Development: This project is suitable for candidates interested in furthering their bioinformatics / biostatistics experience. Candidates undertaking this project will also gain experience in study design, data managements, data analysis, data interpretation and scientific reporting.
Using bioinformatics approaches to unravel the SCN2A neuro-spectrum - also offered as MBiomedSc
Supervisors: Slavé Petrovski and Steven Petrou
Project Site: Department of Medicine RMH, Kenneth Myer Bldg
Contact: Slave Petrovski E: slavep@unimelb.edu.au
Project description: Mutations in SCN2A have emerged as relatively common causes for epilepsy, autism, intellectual disability and even schizophrenia. These represent clinically distinct conditions that often share a very high comorbidity. There are few examples of genes where a given mutation may cause one or a combination of these disorders and it represents a fascinating opportunity to better characterize what properties of SCN2A might result in various clinical presentations. This project will take the bioinformatics lead on the search for patterns of genetic variation linking mutations to the various clinical conditions and will work closely with the Petrou lab that are actively pursuing functional characterization of SCN2A patient and population variants.
Skill Development: This project is suitable for candidates interested in furthering their bioinformatics / biostatistics experience. Candidates undertaking this project will also gain experience in study design, data managements, data analysis, data interpretation and scientific reporting.
Understanding the genetic changes that contribute to neurological disorders - also offered as MBiomedSc
Supervisors: Slavé Petrovski and David Balding
Project Site: Department of Medicine RMH, Kenneth Myer Bldg
Contact: Slave Petrovski E: slavep@unimelb.edu.au
Project description: The human genetics community has made important advances in identifying genes that contribute to disease risk. However, it remains the case that interpreting the roles of individual variant(s) within genes can be difficult. The major goal of this project is to develop and refine tools to accurately classify risk alleles in established disease genes. We will make use of many sources of information in order to achieve a holistic evaluation of the risk of novel variants in established epilepsy genes. These include population genetic analyses of normal genetic variation, predictions of function based on physical and chemical properties of the variant in its context, assessments of phylogenetic conservation across species, and for some genes we will also use experimental read-outs of patient and background variation generated by colleagues working in the wet-lab environment.
Skill Development: This project is suitable for candidates interested in furthering their bioinformatics / biostatistics experience. Candidates undertaking this project will also gain experience in study design, data managements, data analysis, data interpretation and scientific reporting.