Head of research group:

Palle Duun Rohde

Research group name

Genomic Medicine

Initials of research group

GM

Who we are? 

The Genomic Medicine research group is an interdisciplinary team with expertise in molecular medicine, functional genomics, computational biology, quantitative and statistical genetics, biostatistics, and machine learning.

We combine large-scale population genomics with advanced computational modelling and functional validation to understand biological heterogeneity in human disease. By integrating data science and molecular biology, we aim to generate clinically meaningful insight for precision medicine.

The group is based at the Department of Health Science and Technology, Aalborg University, and includes senior researchers, postdoctoral fellows, and PhD students with complementary computational and experimental expertise.

Our research – what we do?

We advance precision medicine by translating large-scale genomic discovery into biologically informed patient stratification across diseases and across the life course.

Our research spans rare monogenic cardiac disorders, psychiatric and neurodevelopmental conditions, cardiometabolic diseases, and neurodegenerative disorders. Across these domains, we focus on shared features such as polygenic architecture, molecular complexity, and clinical heterogeneity.

We develop statistical genetic methods and genomic AI approaches to model complex genetic architectures, integrate multi-omic data, improve risk prediction, and identify disease subtypes. Computational analyses are combined with functional molecular follow-up to move from association toward mechanistic understanding and translational relevance.

How does our research contribute to societal health challenges?

Most common diseases are biologically heterogeneous, and patients with the same diagnosis often differ in underlying mechanisms and treatment response. Traditional approaches based on average effects do not fully capture this complexity.

Our research enables biologically informed patient stratification to improve early detection, risk prediction, and targeted intervention. By integrating genomic discovery with functional validation and translational modelling, we contribute to more precise, equitable, and data-driven healthcare across the life course.