Because we have an interest in the development and application of data mining and machine learning techniques for all single-cell technologies, our team is subdivided into three unique islands.

This ensures a strong focus and specialization on our own topic but also allows for high performance collaborations between the three teams. 

Discover all the accomplishments of the different subteams below!

Our lab is at the forefront of research in computational biology, which is exemplified by a number of major recognitions in the field.  

For example, our tool GenomeView won the 2010 ISMB killer App Award and the ‘Most Creative Visualization’ award in the 2011 Illumina iDEA challenge .  

The algorithms that we develop often also obtain state-of-the-art performance.  As an example, the Genie3 algorithm was the winner of the DREAM5 Network Inference challenge, the most important benchmark for assessing machine learning techniques for systems biology, and the FloReMi algorithm was the best algorithm in the FlowCAP IV challenge on predicting HIV to AIDS progression.  

Our lab is also part of a number of major projects, both in AI research as well as in single-cell research.  We are part of the Human Cell Atlas project (involved in Thymus and Liver cell atlas) and we are also part of the Flanders AI initiative.