Research groups

BIOINFORMATICS CENTRE

Computational Biology

We are interested in the mechanisms of gene regulation and the prediction of RNA and protein structure. Our research encompasses a combination of experimental genomics methods and computational biology including promoter and enhancer analysis, and development of complex probabilistic models to predict, design and validate structure based on machine learning methods.

Anders Krogh, Professor
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In my group we are working to understand the complex mechanisms of gene regulation, where we work on promoter analysis, non-coding RNA, where miRNAs and structure prediction are the main areas. We also work on methods for structure prediction from sequence.
Thomas Hamelryck, Associate Professor
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We are engaged with predicting, designing and determining the 3D structure of RNA and proteins, by developing sophisticated probabilistic models that describe aspects of protein structure. These models are mainly based on machine learning methods (including dynamic Bayesian networks), and directional statistics, the statistics of angles, directions and orientations.
Albin Sandelin, Professor
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The Sandelin lab is a computation/experimental group with scientists from many fields. We focus on gene regulation, transcriptomics, epigenetics and technological and informatics aspects. With the help of computers, we probe large biological datasets that are generated using novel genomics techniques. One of our strengths is our many collaborations with high-profile experimental laboratories, which supply data to be analyzed.
Robin Andersson, Assistant Professor
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The Andersson lab aims to characterize and better understand the architectures of transcriptional regulation and the fundamental properties of enhancers and promoters. In particular, we focus on enhancer transcription and its association with regulatory activity. We take a genomics approach and use computational and statistical learning techniques to model transcriptional regulation based on large-scale sequencing data.
Ole Winther, Professor MSO
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We have two focuses: developing machine learning and AI methods and applying them to genomic data in a clinical setting, and biological sequence analysis and medical informatics. The machine learning research is done with the jointly affiliated group at DTU Compute. Clinical genomic research is carried out in collaboration with Genomic Medicine, Rigshospitalet. An example of a current project is deep generative models for analysis of single cell RNAseq data.
Amelie Stein, Assistant Professor
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Our lab studies the consequences of sequence variants on proteins, focusing on their cellular stability and function. We perform high-throughput assays on protein variants and build on this data to develop and improve methods for prediction of variant consequences. We then apply these methods to determine whether genomic variants are likely to be pathogenic. Further we aim to integrate effects of multiple mutations for applications in protein engineering.

BIOINFORMATICS CENTRE

Population and Statistical Genetics

Our group develops and applies statistical and computational methods for analysis of genomic data in diverse organisms ranging from Greenlandic populations to ruminants and African mammals. We contribute to multiple fields including human and animal disease and treatment, livestock production, migration and speciation processes and complex population analyses.

Hans Siegismund, Associate Professor
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We work on population genetics, phylogeography and speciation processes of large African mammals, mainly bovids and great apes.  Another research area includes the study of evolutionary genetics of Foot-and-mouth disease (FMD) virus in East Africa.
Anders Albrechtsen, Associate Professor
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Our group develops statistical and computational methods for analysis of genomic data including methods for performing multi-loci association studies, methods for detecting and correcting for population stratification, methods for detecting natural selection, loci dependent methods for modeling identity-by-descent and various methods for analysis of second generation sequencing data.
Ida Moltke, Assistant Professor
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We develop and apply statistical methods to genomic data with the purpose of gaining insights into human disease, history and evolution. For instance, by studying DNA from the Greenlandic population we recently identified a genetic variant that explains 10-15% of all cases of type 2 diabetes in Greenland. We have also looked into the migration history of the Artic and are currently investigating how the Greenlanders have genetically adapted the Arctic cold and their very fat-rich diet consisting mainly of seal and fish.
Rasmus Heller, Assistant Professor
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We study evolutionary and population genetics in wild mammals, focusing on ruminants. Our research interests include elucidating how climate, ecosystems and humans have influenced wild mammal populations in Africa, studying adaptive introgression in bovids and exploring how genomic data can be used to aid conservation. We are also involved in a ruminant genome project which aims to understand how ruminants evolved new anatomical structures, and how it has helped them become one of the most successful mammal lineages.

RNA BIOLOGY

We employ and develop molecular, genetic and biochemical approaches to study how RNA-based mechanisms regulate gene expression and cellular development. We focus on RNA structure, RNA modifications and RNA-protein interactions as well as miRNA regulation in plants.

Peter Brodersen, Associate Professor
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Our group studies the mechanisms by which small RNAs regulate gene expression. We use the flowering plant Arabidopsis thaliana as a model system, and make particular use of molecular genetic and biochemical approaches in our work.
Jan Christiansen, Associate Professor
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We are mainly focusing on post-transcriptional events such as RNA localization, RNA stability, and translational control with an emphasis on the role of cytoplasmic RNA-binding proteins expressed during fetal life and oncogenesis.
Jeppe Vinther, Associate Professor
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In our group we aim to determine how RNA structure and RNA-protein interactions affect basal cellular processes. This knowledge is important to understand ways of improving the efficiency and specificity of RNA based drugs.