Analytical Methods for Big High-Dimensional Biomedical Data

Project Details

Modern biomedical data and technology offers unprecedented opportunities for discoveries but also presents novel methodological and computational challenges for data preprocessing, visualisation, analyses and interpretation. We collaborate with leading researchers in the field to address these challenges. Some of the recent methods we developed include normalization and differential expression methods for single-cell RNA-seq data, cost-effective detection of sedentary behaviour using wrist-worn fitbit watch and methods for detecting shift in UACR ratio, an important marker in diabetic patients.

Because the technologies that generate these data are rapidly evolving, so does the nature of the challenges and opportunities in this field. To ensure the relevance of our work, we often need to combine the latest advances in statistical computing and computer science with traditional statistical methods.  Domain-specific knowledge will also be very useful but this is not a requirement for starting higher degree students, rather it can be picked up along the way through close interaction with our collaborators.

More about our lab can be found at www.salimlab.org and we welcome enquiries from highly-motivated students.

Available Higher Degree Projects

  • Prediction of protein translocation using spatial transcriptomics data
  • Removing unwanted variations from spatially-resolved transcriptomics and single-cell multi-omics data
  • Robust and generalizable lipidomics risk prediction models
  • Prediction of sedentary behaviour using smartwatch data

Researchers

Professor Agus Salim

Dr Dulari Hakamuwa Lekamlage

Collaborators

Professor Jonathan Shaw (Baker Institute and Monash University)

Professor Dianna Magliano OAM (Baker Institute and Monash University)

Professor Peter Meikle (Baker Institute and La Trobe University)

A/Prof David Greening (Baker Institute and La Trobe University)

A/Prof David Dunstan (Baker Institute and Deakin University)

Professor Neville Owen (Baker Institute and Swinburne University)

A/Prof Sara Baratchi (Baker Institute)

A/Professor Mirana Ramialison (Murdoch Children’s Research Institute)

Professor Terry Speed (Walter and Eliza Hall Institute)

Professor Jean Yee Hwa Yang (The University of Sydney)

Research Opportunities

This research project is available to PhD students, Masters by Research, Honours students, Master of Biomedical Science, Post Doctor Researchers to join as part of their thesis.
Please contact the Research Group Leader to discuss your options.

Research Group

Biostatistics



Faculty Research Themes

Cancer, Child Health, Infection and Immunology, Neuroscience

School Research Themes

Data science, health metrics and disease modeling, Prevention and management of non-communicable diseases (including cancer), and promotion of mental health



Key Contact

For further information about this research, please contact the research group leader.

Department / Centre

Melbourne School of Population and Global Health

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