Computational statistics applied to population, evolutionary, medical and forensic genetics
Application of mathematical and statistical methods to phylogenetics and evolutionary biology
Irene Gallego Romero
Functional, regulatory and comparative genomics; pluripotent stem cells as systems for genomic studies in non-model mammals
Kim-Anh Lê Cao
Multivariate statistics, ‘omics data integration, feature selection, microbiome, computational statistical learning, R software
Statistical genetics with a particular interest in developing methods for, and applying them to, studies of population structure and immunogenetics
Statistical and computational approaches for the analysis of complex and large-scale genomic data with applications to functional genomics and molecular/trait evolution
Statistical genetics, association analysis, imputation, computational statistics, Bayesian data analysis
Research Manager - Andrew Siebel
Andrew completed his undergraduate BSc(Hons) degree in Zoology and Physiology at The University of Melbourne (1996-1999). His PhD was in the field of Reproductive Endocrinology enrolled through the Department of Zoology, the University of Melbourne and Howard Florey Institute. Andrew then received a prestigious NHMRC Early Career Research Fellowship (2005-2009) to work on developmental programming of adult disease in the Department of Physiology. He moved to the Baker IDI Heart & Diabetes Research Institute in 2009 to work firstly in the Human Epigenetics laboratory, then the Metabolic and Vascular Physiology laboratory (2010-2015). His research interests include cardiovascular physiology, glucose metabolism, lipid biology and interventional clinical trials.
Genomic Data Specialist - Bobbie Shaban
Originally from Perth, Bobbie obtained a double degree in Molecular Biology and Computer Science at Murdoch University. He has worked in a number of Bioinformatics roles including as a bioinformatics officer at the Centre for Comparative Genomics at Murdoch University, the Health Protection Agency UK (Now Public Health England) where he worked on The FF100 Swine flu database and also the Enteric Molecular Typing Network for the 5 nations and at the Australian Genome Research Facility here in Melbourne. In previous roles he was the administrator of the Cluster scheduling software (Sun Grid Engine) and was a Bioinformatician specialising in Genomic Assembly, RNA virus discovery, High performance computing and software pipeline optimisation. He also has experience in Web development, Database admin and creation, a number of computing languages including PERL, PHP and the MVC Frameworks Laravel and Ruby on Rails.
High Performance Compute cluster [helix]
Managed by Bobbie Shaban (Genomic Data Specialist)
384 cores, 3.1Tb RAM, 200Tb storage
Administered by Melbourne Bioinformatics, formerly the Victorian Life Sciences Computation Initiative (VLSCI).
Melbourne Integrative Genomics (MIG), The University of Melbourne, welcomes applications to become an Associate Member (AM). AMs can be researchers at the University of Melbourne or other Parkville research institutes, or any others who have research interests relevant to integrative genomics and can benefit from and contribute to MIG as indicated below.
Benefits of AM status can include:
- Help with UoM Honorary or Visiting Researcher status where appropriate
- Card access to MIG space
- Hot desk space for group leaders (shared office)
- Hot desk space for students & postdocs (open offices)
- Use of meeting room or other bookable rooms
- Infrastructure access (computing allocation)
- Opportunity to contribute to the planning of, and to participate in, MIG activities (such as workshops and seminars)
In return, AMs are expected to:
- Contribute to MIG activities
- Develop collaborations with Core research group members
- If MIG’s resources are used, appropriate affiliation should be included in publications
- Provide photo and brief bio for website
- Contribute to MIG annual reporting as requested
Interested in becoming an Associate Member? Contact the Research Manager for more information.