Data Mining and Modeling for Biomedicine

Our research is situated at the intersection of computer science and biomedical research, with a strong emphasis on the design an application of data mining and machine learning techniques.  We perform fundamental research on robustness and interpretability of machine learning techniques, and focus on applications in biomedicine, translating machine learning applications to the clinic. 

Yvan Saeys

Group Leader
VIB Group leader since 2015
Professor: Ghent Univ., Ghent, Belgium, since 2015
Postdoc: Ghent Univ., Ghent, Belgium, 2009-2013
Postdoc: Univ. Claude Bernard, Lyon, France, 2009
PhD: Ghent Univ., Ghent, Belgium, 2004

Research areas

Computational biology Immunology & inflammation Human diseases

Model organisms

Research Focus

Our research is situated at the intersection of computer science and biomedical research, with a strong emphasis on the design an application of data mining and machine learning techniques.  We perform fundamental research on robustness and interpretability of machine learning techniques, and focus on applications in biomedicine, translating machine learning applications to the clinic.  Many of our applications deal with single-cell technologies, including flow/mass cytometry data, single-cell (multi)omics, and single-cell imaging data types.  Clinical applications include allergies and asthma, rheumatology, cancer (lung cancer and leukemia) and primary immune deficiencies (PID).

Team of Yvan Saeys

Publications

To showcase the world-class scientific research of the Yvan Saeys Lab, you can discover their scientific papers in more detail.

Jobs

We are always on the lookout for highly motivated colleagues to join our team. If you are interested, please contact us.

Team

The Yvan Saeys Lab can only thrive thanks to the dedication and commitment of its people, no matter what their function or seniority.

Events

To stay up to date in rapidly developing fields, scientists regularly interact with (international) colleagues. Conferences and other (scientific) events are an excellent way to facilitate such a continent-spanning knowledge exchange.

Awards

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.