Dick de Ridder
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perform research and teach in the Delft Bioinformatics Lab, part of the Pattern Recognition & Bioinformatics Group, with Marcel Reinders. With a background is in pattern recognition / machine learning, my research goal is to apply adaptive techniques to develop models for molecular biology, primarily based on high-throughput measurement data and available prior knowledge. For an overview of my previous work, please see my curriculum vitae (PDF).

We work together with researchers in medicine, biology and biotechnology to learn about the organisation of life at the molecular level. Our strength is in integrative bioinformatics, i.e. the processing and integration of large high-throughput measurement datasets, for example microarray or mass spectrometry data. We aim at approaches which are applicable -ome-wide, preferably linking several levels of cellular organisation (as in systems biology).

We co-operate with a number of groups, including the labs of Frank Staal at Leiden University Medical Center; Bas Teusink at the Faculty of Earth and Life Sciences, Vrije Universiteit Amsterdam; Hans Roubos of the bioinformatics group at DSM; and the groups of Sef Heijnen and Jack Pronk at the Department of Biotechnology, Delft University of Technology. Our group is part of NBIC, the Netherlands Bioinformatics Centre and the Kluyver Centre for Genomics of Industrial Fermentation.


flag Kernel methods for integrating biological data
as author at  5th IAPR International Conference on Pattern Recognition in Bioinformatics, Nijmegen 2010,