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My group's research uses large-scale genomic data to address knowledge gaps in disease, with a particular focus on cardiovascular disease.

Research programme

1. Cardiovascular disease research using big-data and genomics: with the goal of improving prevention and treatment of cardiovascular disease. By focusing on underrepresented groups, including women, my research aims to also address inequity in cardiovascular outcomes. I am the lead of the South Asian Genes and Health in Australia (SAGHA) study, which aims to increase representation of Australian South Asians in cardiovascular and genomics research. See saghaus.org for further details.

2. Drug genomics: I'm interested in using genomic approaches to predict drug effects, including identification of drug repurposing opportunities as well as identifying unknown adverse effects of medication.

3. Liver transplant research: In this collaboration with the QLD Liver Transplant Unit, we are using genomics to understand the effect of normo-thermic perfusion (a new organ storage method) on liver function, with the long-term goal of improving our ability to predict transplant outcomes.

Career summary: I was awarded my PhD from University College London (UK) in cardiovascular genetics. I began my post-doctoral fellowship under the mentorship of Prof Peter Visscher at the Queensland Brain Institute in 2013. Between 2016-2018, I was the lead analyst for the International Heart Failure Genetics Consortium (HERMES). In 2018, I was awarded an NHMRC Early Career Researcher Fellowship to investigate the relationship between cardiovascular and brain-related disorders using large-scale genetic and genomic data, under the mentorship of Prof Naomi Wray, and subsequently two consecutive National Heart Foundation Future Leader Fellowships, establishing the Genomics in Health lab in 2023.

Recognition:

2025 UQ Research Culture Award for Advancing Inclusive Research Environments

2024 Australian Academy of Science Ruth Stephens Gani Medal for outstanding contribution to genetics research

2023 1 of 5 global finalists for the Nature Inspiring Women in Science (Scientific Achievement Award)

2023 Lifesciences QLD Rose-Anne Kelso Award

2023: Named in Australia's Top 25 Women in Science by Newscorp

2022 Queensland Young Tall Poppy Award

2022 UQ Foundation Research Excellence Award

2021/2022 Australian Superstar of STEM,

2020 Genetic Society of Australasia Early Career Award

2020 Women in Technology Rising Star Science Award

Peter Simpson is a recognised expert in the molecular and pathological characterisation of breast and lung cancers. His research is based at the UQ Centre for Clinical Research (UQCCR), where he is the Head of the Cancer Theme and is a Research Group Leader in Cancer Genomics. He has published >150 articles (>12,000 citations, H-index 52; Scopus, May2025) including in Nature, Nature Medicine, Annals of Oncology and the American Journal of Respiratory and Critical Care Medicine. He co-manages the Brisbane Breast Bank (BBB), a tissue bank created to facilitate clinical breast cancer research, and the Debutant lung cancer Program.

Pete also holds a teaching appointment in UQ, where he is passionate about the science and clinical applications of Pathology. He teaches into the UQ Medical Program (Year 1 and 2), as well as to undergraduates. He has co-authored a chapter ‘Breast Diseases’ in the latest edition (11th) of the internationally acclaimed Medical text book Robbins and Cotran Pathologic Basis of Disease.

Outside UQ, Pete is a Fellow of the Faculty of Science in the Royal College of Pathologists of Australasia (FFSc RCPA), a member of the kConFab Executive (https://www.kconfab.org/), a member of the Lobular Breast Cancer Alliance Scientific Advisory Board (https://lobularbreastcancer.org/), and a member of the International Cancer Genome Consortium (Breast Cancer group).

Pete enjoys supervising students at all levels in their careers and collaborating within multidisciplinary teams spanning clinical (e.g. pathology, oncology) and science teams (e.g. in ‘omics, bioinformatics and machine learning).

Critical Care Medicine focuses on supporting patients, often with one or multiple organ failures. Based at the largest Australian cardiac hospital, our research investigates better ways to support patients with heart and/or lung failure. We explore technological, pharmacological and engineering advances that could help our patients to live longer and better. Our group is world-renowned for clinically relevant large animal models, including heart failure, respiratory failure (ARDS), heart transplantation, sepsis, cardiogenic shock, and more. All our studies use hospital-grade equipment and follow the same clinical guideline to maximise translation. We actively take on honours, MPhil and PhD students from multi-disciplinary backgrounds (science, engineering, medicine, allied health), with a successful track record in supporting our students to secure their own grants and funding. Students are expected to contribute to other studies of the group. For more information about the group, please visit ccrg.org.au, and email if you are interested to join us.

I am a computational biologist specialising in the integration of multi-omics data to study rheumatoid arthritis (RA). My research combines clinical data, serum proteomics, single-cell transcriptomics, and spatial transcriptomics to understand disease progression, patient trajectories, and flare events.

I am particularly interested in the immune landscape of synovial tissue and how spatial organisation of immune and stromal cells contributes to inflammation and remission. Through advanced statistical modelling and machine learning, including clustering and trajectory inference, I aim to identify predictors of flare and uncover mechanisms that drive differences in patient outcomes.

Alongside my work in RA, I also investigate the link between systemic inflammation and cardiovascular disease, applying spatial, single-cell transcriptomics, proteomics and bioinformatics approaches to explore how chronic inflammation contributes to cardiac dysfunction.

The overarching goal of my research is to improve early prediction of disease trajectories, support personalised management strategies, and contribute to the development of targeted therapies for patients with RA.

Associate Professor Kelvin Tuong is an NHMRC Emerging Leadership Fellow and Deputy Director and group Leader of the Ian Frazer Centre for Children’s Immunotherapy Research (IFCCIR), Child Health Research Centre. He is interested in single-cell analysis of immune cells and harnessing adaptive immune receptors for understanding immune cell development and function in health and in cancer.

A/Prof Tuong was born and raised in Singapore and moved to Brisbane, Australia, after completing national service in Singapore and obtaining a Diploma in Biomedical Laboratory Technology (Ngee Ann Polytechnic).

A/Prof Tuong was originally trained as a molecular cell biologist and gradually transitioned into bioinformatics during his post-doctoral training. He has been very prolific for an early career researcher, having published >70 articles since 2013, with nearly a third of them as first/co-first or last author and has a stellar track record of pushing out highly collaborative work in prestigious journals including Nature, Cell, Science, Nature Medicine, Nature Biotechnology J Exp Med etc. He has the rare combination of having excellent laboratory and bioinformatics skill sets which provide him a strong command of both fundamental immunology and computational approaches.

A/Prof Tuong completed his undergraduate Bachelor's degree in Biomedical science with Class I Honours, followed by his PhD in macrophage cell biology and endocrinology at UQ (Prof Jenny Stow lab and Emiritus Prof George Muscat lab, IMB, UQ). He then went on to a post-doc position with Emiritus Prof Ian Frazer (co-inventor of the Gardasil cervical cancer vaccine, UQ Frazer Institute, Translational Research Institute) where he worked on HPV immunology, cervical cancer and skin cancer. In his time in the Frazer lab, he developed an interest in bioinformatics analyses as a means to tackle and understanding immunology problems in health and disease. He then moved to the UK and joined Prof Menna Clatworthy's lab at the University of Cambridge and Prof Sarah Teichmann's lab at the Wellcome Trust Sanger Institute. He has focused his interests on single-cell analyses of tissue immune cells, including T and B cells and their specific receptors (TCR/BCR). He has developed bespoke bioinformatics software, including one tailored for single-cell B Cell Receptor sequencing analysis, Dandelion, which he used in one of the largest combined single-cell transcriptomic, surface proteomic and TCR/BCR sequencing dataset in the world, published in Nature Medicine, and more recently in Nature Biotechnology where we introduced a TCR-based pseudotime trajectory analysis method.

A/Prof Tuong is now leading the Computational Immunology group at the IFCCIR and his lab is focused on investigating how pediatric immunity is perturbed during cancer at the cellular level and how this information can be used for creating novel warning systems for children with cancer. For potential students/post-docs/trainees interested in joining the team, please contact A/Prof Tuong at z.tuong@uq.edu.au.

Dr. Akila Wijerathna-Yapa is an interdisciplinary Biotechnology scientist and Postdoctoral Research Fellow at the Frazer Institute, University of Queensland, with over 12 years of expertise spanning Biochemistry, Molecular Biology, and Bioinformatics. Holding a PhD in Biochemistry from The University of Western Australia, an MSc in Molecular Biology from The Hebrew University of Jerusalem, an MBA from the University of Staffordshire, and B.Sc. (Hons.) Sp. Biotechnology from The Wayamba University of Sri Lanka, he brings a rare combination of deep scientific expertise and strategic project management insight to the life sciences.

Dr. Wijerathna-Yapa's research is defined by his ability to integrate advanced technologies—including mass spectrometry-based proteomics, peptidomics, metabolomics, lipidomics, NMR spectroscopy, and transcriptomics—to unravel molecular complexities and translate multi-omics data into actionable insights. His work spans molecular biology, cell culture bioprocess optimisation, clinical biomarker discovery, and spatial biology, with postdoctoral experience at The University of Queensland and Dalhousie University, and collaborative partnerships with leading research institutions across Sri Lanka, China, Israel, Australia, and Canada.

With a strong foundation in advanced statistical data analysis and a proven track record in project management and scientific communication, Dr. Wijerathna-Yapa bridges the gap between scientific discovery and practical innovation. He has authored over 25 peer-reviewed publications and has been recognised with prestigious international awards including the Australian Government Global Talent Independent visa and fellowships from the Higher Education Academy (FHEA, UKPSF). He is passionate about leveraging interdisciplinary knowledge to drive transformative advancements in biotechnology and life sciences.

Dr Jian Zeng is a statistical geneticist, NHMRC Emerging Leadership Fellow and Group Leader at the Institute for Molecular Bioscience, The University of Queensland. His research uses large-scale genomic data to understand the genetic basis of complex traits and diseases, improve polygenic risk prediction, and identify the genes, cell types and biological processes through which genetic risk acts.

His group develops statistical methods and software tools across four interconnected areas:

• genetic architecture and evolutionary signatures of complex traits;
• polygenic prediction within and across diverse populations;
• fine-mapping of causal genetic variants and genes;
• integration of human genetics with functional and single-cell genomics.

This work addresses major challenges in statistical genetics and precision medicine, including the analysis of whole-genome sequencing data, the reduced accuracy of genetic prediction in underrepresented populations, and the biological interpretation of disease-associated variants. His methods are translated into accessible software used by researchers internationally and are applied to psychiatric, neurological, metabolic and other complex diseases.

Dr Zeng received the IMB Impact Award for Enabling Technology and Method Development in 2021 and the UQ Foundation Research Excellence Award in 2025.

I am a senior bioinformatician at the Institute for Molecular Bioscience, The University of Queensland, with over 20 years of experience in next-generation sequencing (NGS) data analysis. My career began with the greenfield development of three major NGS platforms: 454, Illumina, and SOLiD. This early experience laid the foundation for my extensive expertise in bioinformatic analysis across a wide range of NGS data types.

While bioinformaticians are often positioned in service-oriented roles, my work has consistently extended beyond service delivery. For example, as the leader of the bioinformatics core facility at the Queensland Brain Institute from 2012 to 2022, my primary responsibilities included providing bioinformatics support, but I also actively contributed to project design, supervised PhD and Master’s students, and maintained a strong research profile.

To date, I have authored 45 peer-reviewed publications, with more than one-third as first, co-first, or last author. According to SciVal, over 57.8% of my publications rank in the top 10% most cited in their respective fields. My research spans the development of novel bioinformatics tools, such as the TRIAGE R package for regulatory analysis of both bulk and single-cell RNA-seq data (Briefings in Bioinformatics, 2025), as well as studies in single-cell transcriptomics (Nature Communications, 2025; Developmental Cell, 2024), lncRNA analysis (Molecular Psychiatry, 2024; Nature Communications, 2023), integrative analysis of ATAC-seq and lncRNA data (Cell Reports, 2022), de novo transcriptome assembly (Development, 2022), noncanonical Z-DNA structure analysis (Nature Neuroscience, 2020), m6dA DNA modification analysis (Nature Neuroscience, 2019), whole-exome sequencing analysis (Genome Medicine, 2017), and cross-ethnic meta-analysis (Nature Communications, 2017), reflecting a broad and sustained contribution across multiple areas of genomics and computational biology.