About
Dr Md Rezanur Rahman is a postdoctoral Research Officer in the Neurogenetics and Dementia Group at QIMR Berghofer.
Dr Rahman obtained his PhD in bioinformatics and statistical genetics at The University of Queensland, Australia, supported by the internationally competitive Research Training Program Scholarship. His doctoral research investigated the molecular mechanisms underlying neuronal homeostatic plasticity and Alzheimer's disease by integrating transcriptomic, epitranscriptomic, and genome-wide genetic approaches. He also holds Honours and Master's degrees from Islamic University, Bangladesh, where his research specialised in bioinformatics and systems biology. His academic achievement was recognised nationally with the Bangladesh Prime Minister's Gold Medal (2017).
Before beginning his PhD in Australia, Dr Rahman was a Lecturer at Khwaja Yunus Ali University, Bangladesh. His current work focuses on the genetic architecture and molecular pathways
underlying Alzheimer's disease and related complex traits. He applies statistical genetics, genome-wide association studies, polygenic risk score prediction, Mendelian randomisation, and multi-omics integration to identify disease mechanisms, biomarkers, and potential therapeutic targets.
Dr Rahman has authored more than 40 peer-reviewed articles in international journals, with expertise spanning statistical genetics, neuroimaging genetics, bioinformatics, and translational genomics. His overarching goal is to translate genetic discoveries into biological insight and improved therapeutic strategies for neurodegenerative diseases.
Research Skills
- Statistical genetics
- Polygenic risk prediction
- Genome wide association study
- Neuroimaging genetics
- Systems genetics
- bioinformatics
Area of Interest
- Multi-omics data integration to gain insights
into disease risk and therapeutic targets - Translational research focused on biomarker
discovery and drug repurposing - Systems genetics approaches to infer causal
pathways and mechanisms underlying comorbidities - Genetic association studies (GWAS) to identify
risk loci and causal genes