🎓 Discover PhD and Master's programmes at leading universities worldwide — Sign up free to save searches and get email alerts
MUM

Precision blood-cell biomarkers for early prediction of severe dengue

Monash University Malaysia Medicine and Health Sciences
✓ Funded (Competition) 🎓 Bioinformatics 🎓 Health Sciences 🎓 Medicine machine learning multi-omics immunology dengue biomarkers cytof citeks-seq clinical research

Explore blood-cell biomarkers to predict severe dengue early using advanced multi-omics techniques and AI integration. Collaborate internationally and develop diagnostic tools to improve patient outcomes.

AI-generated overview

🌍
Why This Research Matters

Early prediction of severe dengue through blood-cell biomarkers can transform clinical management by enabling timely therapeutic interventions, reducing mortality and severe complications. This research supports the development of practical diagnostic tools for use in endemic regions, impacting public health and healthcare resources globally.

Infectomics Microbiology Virology IFN Signaling Protein-protein interactomics

Project Description

Project Overview

This project will establish a prospective dengue cohort at University Malaya Medical Centre to identify early blood-cell signatures predicting severe dengue disease. Peripheral blood samples will be collected at first patient presentation; PBMCs and plasma will be processed and cryopreserved. Fresh-blood immunophenotyping including neutrophils will be done locally in Kuala Lumpur, and cryopreserved samples will be sent to Melbourne for advanced CyTOF and CITE-seq profiling. Machine learning will integrate data to develop a compact biomarker panel suitable for point-of-care diagnostics.

What You Will Do

You will conduct clinical and biobank-linked research involving immunology, animal cell culture, and core molecular biology techniques. You will perform rigorous data documentation, management, and scientific writing. You will analyze multi-omics data with preference for experience in R/Python and will receive cross-site co-supervision and training with the Monash Biomedicine Discovery Institute.

Expected Outcomes

The project aims to deliver a validated predictive biomarker signature and an industry-ready analytical pipeline, supported by a joint clinical, immunology, and bioinformatics team. This will facilitate early diagnosis and improved clinical management of severe dengue cases.

Why This Matters

Dengue is a major global health concern, especially in tropical regions. Early identification of patients at risk of severe disease could significantly improve treatment outcomes and reduce mortality. This research will provide novel biomarkers and diagnostics tools to help clinicians make timely decisions, potentially saving lives and reducing healthcare burdens.

Entry Requirements

Minimum academic qualification of First Class Honours (H1) or equivalent recognized by Monash University Malaysia. Prior experience in immunology and clinical or biobank-linked research, competence in animal cell culture and molecular biology techniques, rigorous documentation and data management skills. Familiarity with R/Python and omics data analysis preferred.

How to Apply

Contact the main supervisor with your academic background and achievements to determine suitability. If a fit, complete an Expression of Interest (EoI) including a research proposal relevant to this GEMS project. Eligible candidates will be invited to apply for PhD candidature and may be selected for interview. Interviews expected in March 2026 with notifications shortly after.

Eligibility

UK/Home
EU
International

Supervisor Profile

AP
Assoc Prof Vinod Balasubramaniam
Monash University Malaysia, Medicine and Health Sciences
3103 Citations
24 h-index
Google Scholar

Assoc Prof Vinod Balasubramaniam is a Group Leader at the Jeffrey Cheah School of Medicine and Health Sciences, Monash University Malaysia. His research focuses on Infectomics, Microbiology, Virology, and interferon signaling pathways using protein-protein interactomics approaches. He combines clinical immunology with molecular biology to understand virus-host interactions, notably in flavivirus infections.

Key Publications

2016 969 citations
Zika virus targets human STAT2 to inhibit type I interferon signaling
Identified how Zika virus evades the immune system by targeting human STAT2.
2018 388 citations
Comparative flavivirus-host protein interaction mapping reveals mechanisms of dengue and Zika virus pathogenesis
Revealed molecular mechanisms underlying dengue and Zika virus pathogenesis through protein interaction mapping.
2017 282 citations
A novel Zika virus mouse model reveals strain specific differences in virus pathogenesis and host inflammatory immune responses
Developed a mouse model demonstrating strain differences in Zika virus effects and immune responses.
2021 212 citations
Hyperinflammatory immune response and COVID-19: a double edged sword
Discussed the dual role of hyperinflammation in COVID-19 severity and progression.
2019 188 citations
Enlightening the role of high mobility group box 1 (HMGB1) in inflammation: Updates on receptor signalling
Provided updated insights into HMGB1's role and signaling pathways in inflammation.

Research Contributions

Demonstrated that Zika virus targets human STAT2 to inhibit type I interferon signaling.
This finding provides crucial insights for developing antiviral strategies targeting immune evasion mechanisms.
Mapped flavivirus-host protein interactions revealing differences in dengue and Zika virus pathogenesis.
Advanced the understanding of flavivirus infections contributing to improved therapeutic approaches.
Developed a novel mouse model to study Zika virus strain-specific pathogenesis and immune responses.
Enabled preclinical evaluation of vaccines and treatments tailored to different Zika virus strains.
Reviewed the role of hyperinflammatory immune responses in COVID-19 disease progression.
Informed clinical management strategies to balance immune responses in COVID-19 patients.

Related Opportunities

Computational Genomics Approaches to Understanding Human Diseases and Cancer
University of Oklahoma College of Medicine Dr. Qingnan Liang 🎓 Bioinformatics 🎓 Genetics

Explore the interface of computational and experimental genomics to unravel cancer mechanisms. Develop innovative software and analyze vast omics datasets. Join a lab committed to mentorship, cutting-edge research, and …

This research is critical for understanding complex genomic alterations in diseases such as cancer, enabling improved diagnostic and therap…

Computational Genomics Cancer Research Multiomics Data Mining Bioinformatics Software
AI-based Prediction of Protease Cleavage and Kinetics in Protein Digestion
Wageningen University and Research Dr. Gijs Vreeke 🎓 Bioinformatics 🎓 Computational Biology Deadline: 26 May 2026

Explore the application of AI to model protease cleavage sites and peptide release during protein digestion. Develop data-driven kinetic models using advanced LC-MS experimental data to better understand and predict foo…

This research advances the understanding of protein digestion, critical to optimizing nutritional value and bioavailability of dietary prot…

peptides LC-MS protein hydrolysis digestive proteases
AI-Aided Data-Driven Study of Historical Parchments' Making, Degradation, and Origin
Nottingham Trent University Professor Haida Liang 🎓 Analytical Chemistry 🎓 Bioinformatics

Explore how AI and advanced imaging can unlock secrets of historical parchments' origins and preservation. Develop data-driven tools to identify parchment species and assess degradation without damaging valuable manuscr…

This research enables preservation of key historical documents by developing non-invasive, AI-driven tools to evaluate parchment origin, ag…

Parchment Degradation Machine Learning Optical Imaging Cultural Heritage Conservation
Optimising Extrusion and Printability for 3D-Printed Oral Solid Dosage Forms
Aston University Dr Daniel Kirby 🎓 Health Sciences 🎓 Materials Science

Explore extrusion and formulation strategies to improve 3D printing of personalised oral medicines. Investigate hardware and material controls to enhance print quality and manufacturing scalability for pharmaceutical ap…

This research improves the reliability and scalability of 3D printing for personalised oral medicines, potentially transforming pharmaceuti…

Additive Manufacture Extrusion Control Pharmaceutical Formulation Process Analytics