Simon Rasmussen

To solve fundamental biological questions related to human health and disease it has become apparent that we must study them from multiple angles using multi-omics and multi-modal data. This is especially important for complex phenotypes such as cardio metabolic diseases.

Associate Professor Simon Rasmussen explains: “Our research aims to develop advanced bioinformatics and computational methods based on recent advances in artificial intelligence. By learning across multiple types of data we are able to better understand diseases and work towards precision health”.

In particular the group focus on analysis of multi-omics data such as genomics, proteomics, microbiome data, clinical records, and electronic health data. By bringing all of this information together we want to translate biological and medical knowledge to the clinic.