Genomics and medical bioinformatics

Rich datasets


Genomics allows us to study cells and organisms at unprecedented resolution. A single experiment can reveal the entire genome or provide millions or even billions of data points on gene expression, epigenetics, chromatin conformation, or numerous other aspects of cellular state. Given the volume of data, computational analysis is a key aspect of genomics. With proper computational analysis, these rich datasets can reveal both system-wide properties and details of individual molecular components.

Molecular characterization

When applied to medical samples and integrated with clinical data, genomics and bioinformatics become powerful tools for studying the molecular basis of disease. They allow the identification of molecular phenotypes associated with disease and potentially patient outcome. Molecular characterization provides novel methods for patient stratification and potentially improved treatment through refined precision medicine approaches.
Bioinformatics analysis can also reveal the genetic causes of diseases, with identification of the specific variants and mutations that underlie genetic disorders, disease susceptibility, or cancer development.

Precision medicine 

Today, medicine is undergoing a transformation towards personalized treatment. At the heart of this transformation is bioinformatics and high-throughput data acquisition and analysis, particularly based on Next Generation Sequencing (NGS). Combined these developments drive the field of precision medicine now being implemented across clinical disciplines, with improved diagnostics and prognostics based on molecular tests promising personalized treatments with fewer side-effects and better response rates. 


Bioinformatics at MOMA


The Bioinformatics groups at MOMA use large medical data sets to study cellular processes, disease development, and clinical applications.
Current research topics include cancer evolution, mutational processes (in both cancer and germline), gene regulation, and clinical outcome prediction. Research projects are typically based on existing large genomics data sets from public or local sources complemented with project-specific data generation. Projects span statistical method development, implementation and software development, interpretation and hypothesis generation, experimental validation, and clinical translation.

Collaborations and facilities

We collaborate closely with the clinical and experimental groups at MOMA. We also have close ties and dual affiliations with the Bioinformatics Research Centre (BiRC) at Faculty of Science and Technology, Aarhus University.
MOMA houses a state-of-the-art Next Generation Sequencing facility. We share extensive genomics infrastructure with the diagnostic unit at MOMA maintained by staff bioinformaticians. We are part of the Aarhus Center for Genomics and Personalized Medicine and have access to the high performance computing (HPC) facility at Aarhus University with 5K nodes and >7PB storage.