Melbourne Integrative Genomics
Melbourne Integrative Genomics (MIG) is an interdisciplinary initiative of the University of Melbourne
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MIG News & Research Highlights
About MIG
We aim to understand biological systems, with a focus on genomes as the blueprint for each system. We are interested in biological systems of different scales, including molecular systems, cell systems, individuals, host-pathogen interactions, species interactions, and populations. For more details see our Research page.
MIG is co-hosted by the School of BioSciences and School of Mathematics & Statistics. We are supported by the Faculty of Science and Deputy Vice-Chancellor (Research) and work closely with Melbourne Bioinformatics and the Computational Biology Research Initiative.
Research Groups
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David Balding
Computational statistics applied to population, evolutionary, medical and forensic genetics
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Yao-ban Chan
Application of mathematical and statistical methods to phylogenetics and evolutionary biology
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Irene Gallego Romero
Functional, regulatory and comparative genomics; pluripotent stem cells as systems for genomic studies in non-model mammals
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Kim-Anh Lê Cao
Multivariate statistics, ‘omics data integration, feature selection, microbiome, computational statistical learning, R software
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Stephen Leslie
Statistical genetics with a particular interest in developing methods for, and applying them to, studies of population structure and immunogenetics
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Davis McCarthy
Computational statistics, statistical genetics and bioinformatics, multi-omic data analysis
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Heejung Shim
Statistical and computational approaches for the analysis of complex and large-scale genomic data with applications to functional genomics and molecular/trait evolution
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Michael Stumpf
Statistical, mathematical, evolutionary and functional analysis of molecular interaction networks and dynamical processes in biological systems
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Damjan Vukcevic
Statistical genetics, association analysis, imputation, computational statistics, Bayesian data analysis
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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.
Follow Bobbie's MIG I.T. blog here. -
PhD Students
Katalina Bobowik
Project title: Transcriptomic characterisation of immune and disease-related traits within Island Southeast Asia
Github link
Supervisor: Irene Gallego RomeroSusan Ellul
Project title: Statistical methods for longitudinal microbiome data
Google scholar link
Supervisor: Kim-Anh Lê CaoQian Feng
Project title: Phylogenetic modelling of malaria var genes
Github link
Supervisor: Yao-ban Chan/Heejung ShimAnubhav Kaphle
Project title: Statistical methods for trans-ethnic genetic studies
Google Scholar link
Supervisor: David BaldingAli Mahmoudi
Project title: Inference under the coalescent with recombination
Github link
Supervisor: David BaldingElisabeth Roesch
Project title: Hybrid modeling in Systems Biology
Github link
Supervisor: Michael StumpfGeorgia Tsambos
Project title: Statistical techniques for studying admixture and local ancestry
Github link
Supervisors: Damjan Vukcevic & Stephen LeslieDavide Vespasiani
Project title: Functional analysis of archaic variants in modern Indonesians
Google scholar link
Supervisor: Irene Gallego RomeroYiwen (Eva) Wang
Project title: Managing batch effects in microbiome data
Github link
Supervisor: Kim-Anh Lê Cao
STAFF & STUDENTS
| Postdocs | Students |
| Aleks Dakic (Lê Cao) | Laura Cook (PhD - Gallego Romero) |
| Ashley Farlow (Leslie) | Megan Coomer (PhD - Stumpf) |
| Anissa Guillemin (Stumpf) | Leo Diaz (PhD - Stumpf) |
| Lucy Ham (Stumpf) | Anna Farre Orteu (PhD - Gallego Romero) |
| Abolfazl (Al) JalalAbadi (Lê Cao) | River Kano (MSc - Gallego Romero) |
| Sudaraka Mallawaarachchi (Balding) | Brendan Law (MSc - Shim) |
| Allan Motyer (Leslie) | Chengyu Li (PhD - Balding) |
| Puxue Qiao (McCarthy) | Quiyi Li (PhD - Chan) |
| David Squire (Leslie) | Jiangrong Ouyang (MSc - Shim) |
| Jeff Paril (PhD - Balding) | |
| Recent Visitors | Yinghua Shen (MSc - Lê Cao) |
| Garrett Hellenthal (University College London, UK) - April-June 2019 | Denny Shin (MSc - Shim) |
| Murray Cox (Massey University, New Zealand) - February-March 2019 | Matthew Silcocks (PhD - Leslie/Farlow) |
| Hanaisa Sant'Anna de Pla (Universidade Federal de Minas Gerais, Brazil) - August 2018-August 2019 | Manu Yadav (MSc - Chan/Shim) |
| Sebastien Dejean (Toulouse University, France) - July-August 2018 | Yupei You (PhD - Shim) |
| Jukka Corander (University of Oslo and University of Helsinki, Finland) - December 2017-January 2018 | |
| Tatiana Hessab (Perito Criminal do IPPGF, Rio de Janeiro Area, Brazil) - July 2017-January 2018 | |
| Laetitia Cardonnna (IRSTEA, France) - November-December 2017 & April 2019 | |
| Olivier Chapleur (IRSTEA, France) - September-December 2017 & April 2019 | |
| Solange Pruilh (INSA Toulouse, France) - July-September 2017 | |
| Doug Speed (Aarhus University, Denmark) - April-May 2017 | |
| Paul O'Reilly (King's College London, UK) - April 2017 | |
| John Whittaker (GSK, UK) - April 2017 | |
ASSOCIATE MEMBERS
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.
Meet our Associate Members
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.
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).
Past events
Research projects available to undergraduate and postgraduate students
We offer a range of Hons, MSc and PhD student projects with computational biology and genomics research themes
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Multivariate computational methods for data integration of single cell assays
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Machine learning methods for mRNA alternative splicing
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2D multi-scale approaches for analysis of high-throughput sequencing data
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Treelets-based approaches to estimating sparse fine-scale population structure from genetic data
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Predicting stem cell behaviour
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Finding signatures of cell identity in Stemformatics
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Genome-wide models for heritability and prediction
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Quantifying genetic variation across multiple populations
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Forensic weight-of-evidence for unilineal markers
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Gaussian process regression for ABC inference
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The population history of indigenous Australians: what can the available genetic data tell us?
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Inference of RNA binding proteins (RBP) occupancy transcriptome-wide
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Statistical approaches for analysis of ribosome profiling data: regulation of stop codon readthrough during protein translation
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Better predictions of transcription factor activity in footprinting
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Developing a comprehensive chimpanzee transcriptome
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Reconciliations of gene and species phylogenies
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Mathematical modelling of recombination between gene duplicates
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A time-course ‘omics multivariate data analysis framework
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Overall model fit criteria for multivariate integrative models
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Genetic diversity in public chimpanzee data sets: truly representative of the species?
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How robust are gene regulatory networks across populations?
We create and distribute software and IT tools for the computational biology research community
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KIR*IMP
The KIR*IMP method will allow you to impute various KIR types using your data, including KIR gene copy number, KIR A or B haplotype and gene-content haplotypes.
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LDAK
Fast computation of LD-Adjusted SNP weights and Kinship matrices for genome-wide mixed-model analysis. Includes a generalised REML Solver and efficient gene-based association testing.
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likeLTD
likeLTD is an R package for computing likelihoods for DNA profile evidence, including complex mixtures and when profiles are subject to dropout.
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mixOmics
mixOmics is an R toolkit for the multivariate analysis of biological data, with a specific focus on ‘omics data integration and variable selection.
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multiBLUP
The best genomic predictor we can find, for individual genotype data and both binary and quantitative traits. Generalises the classical BLUP approach and largely retains its computational efficiency.
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mvBIMBAM
BIMBAM for genetic association analysis of multiple related phenotypes.
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WaveQTL
Wavelet-based genetic association analysis of functional phenotypes arising from high-throughput sequencing assays.
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MTR-Viewer
The Missense Tolerance Ratio measures the purifying selection acting on missense variants. Interactive plots and downloads available for 18,000+ genes.
Genomic Databases Resource Hub
Melbourne Integrative Genomic’s I.T. blog (COGENT) is a genomic resource hub used to store tutorials, information about genomic databases and contact information that is regularly used by our group and collaborators. COGENT contains video recordings of our fortnightly computational tutorials and in-depth background on major genomic datasets available online, managed by Bobbie Shaban (Genomic Data Specialist, MIG).
Statistical Genetics Online Lecture Series
Location
Melbourne Integrative Genomics (MIG) is located on Royal Parade at the University of Melbourne’s main Parkville campus (Building 184), a 20 minute walk or short tram ride (Route 19, Stop no. 11) from the city centre.
Mailing address
Melbourne Integrative Genomics
Building 184, Royal Parade
University of Melbourne
Parkville 3010, Victoria, Australia
Contacts
| David Balding (Director) | Phone: 8344 3730 | Email: david.balding@unimelb.edu.au |
| Andrew Siebel (Research Manager) | Phone: 8344 0707 | Email: asiebel@unimelb.edu.au |
| Bobbie Shaban (Genomic Data Specialist) | Phone: 8344 8731 | Email: babak.shaban@unimelb.edu.au |
