Computational Science and Genomics

The Doherty Institute is home to teams with significant expertise in genomics, including the Centre for Pathogen Genomics, Microbiological Diagnostic Unit Public Health Laboratory, Victorian Infectious Diseases Reference Laboratory, and research groups in the Departments of Microbiology and Immunology (DMI) and Infectious Diseases (DID) at the University of Melbourne.

These teams use leading sequencing technologies and computational sciences to decode the genetic makeup of viruses and bacteria in specimens. Collectively, this is used to identify and diagnose known and novel pathogens, track outbreaks and predict their source, and understand how pathogens adapt – through mutation, recombination, or resistance to antimicrobial therapies. This is driving new or improved diagnostic tests, more effective treatments, and informing clinical and public health responses to pathogens.   

The utility of genomics to monitor how pathogens evolve and spread is a critical tool for infectious disease surveillance. MDU PHL’s development and implementation of the AusTrakka platform has been critical in enabling real-time sharing and analysis of pathogen genomic data across Australia, supporting coordinated outbreak surveillance at both state and national levels. 

 In addition to its domestic impact, the Doherty Institute – through MDU PHL and the VIDRL – contributes to strengthening regional surveillance capacity. These teams lead international training programs and collaborative initiatives, particularly across the Asia-Pacific, helping build global capability in microbial genomics and public health response. 

Genomics enables researchers at the Doherty Institute to track how bacteria and viruses evolve, revealing mutations and adaptations that impact disease and treatment. A key focus is antimicrobial resistance, where sequencing uncovers the genetic changes that allow bacteria like Staphylococcus aureus to survive antibiotics. Platforms like InToxSa combine genomic and microbiological data to understand how these pathogens evade immune responses, guiding the development of targeted therapies and public health strategies. 

Genomic technologies are being translated into clinical and public health tools, improving diagnostics, vaccine development, and disease management. For example, RNA-based diagnostics are revolutionising paediatric care by enabling rapid fever diagnosis. Genomic standards are also being established for public health applications, such as tuberculosis elimination, ensuring consistent and effective use of sequencing data in healthcare settings. 

The Doherty Institute employs leading multi–omics technologies to explore pathogens and the host response during both health and disease. . Data can originate from host and/or pathogen bulk, single cell and spatial tissue samples. Various omics data sets are also integrated for collective analyses together with clinical and experimental data. Computational scientists across the Doherty Institute are skilled at analysing different omics data including the Doherty Computational Sciences Initiative (CSI), Centre for Pathogen Genomics, and groups across various  Departments. . These analyses are driving critical insights into understanding immune responses during health and various diseases, and pathogen or cancer countermeasures. This is allowing novel targets to be identified for therapeutic intervention.   

Computational science, including AI and machine learning, plays a vital role across research at the Doherty Institute. These tools help predict viral mutations, trace outbreak origins, and analyse complex biological data. In genomics, they support rapid identification of emerging variants and resistance traits. Beyond genomics, these methods are used to model immune responses, improve RNA-based diagnostics, and study cancer immunotherapy. 

To support large scale computational research, the Doherty Institute houses multiple computational groups and platforms. This expanding collection of computational scientists includes bioinformaticians, statisticians, epidemiologists, machine learning specialists and software engineers. They use high performance computing infrastructure located in-house or at the University of Melbourne – Research Computing Services for high-throughput data analyses. This enables analytical tools to be developed and deployed, ensuring analyses are scalable and impactful.   

Training is a key focus. Workshops, seminars, help sessions and symposia are held to build skills in bioinformatics, biostatistics, and other computational methods to analyse data from researchers, clinicians, and public health professionals. Moreover, the next generation of computational scientists are being trained via Masters and PhD programs. These efforts also extend globally through partnerships and capacity-building initiatives, strengthening pathogen genomic surveillance and research capabilities in regions such as the Asia-Pacific.