Prof. Dr. Peter Dawyndt heads the Computational Biology Lab at the Faculty of Sciences (Department of Applied Mathematics, Computer Science and Statistics), whose research occurs at the intersection of computer science and the life sciences. This cross-fertilization is a potential starting point for fundamental new developments in biology, biotechnology and medicine, but also serves as a source of inspiration for novel developments in computer science. Among the current research topics are computational applications for (meta)genomics, (meta)proteomics, (meta)transcriptomics, (bio)chemistry and data visualization. His group currently actively works on the development of the Unipept platform and the Dodona platform.
Keywords: computational biology, bioinformatics, computer science, educational data mining, learning analytics
Martens S, Landuyt A, Espeel P, Devreese B, Dawyndt P, Du Prez F (2018). Multifunctional sequence-defined macromolecules for chemical data storage. Nature communications 9(1), 4451.
Mesuere B, Devreese B., Debyser G., Aerts M., Vandamme P., Dawyndt P. (2012). Unipept: tryptic peptide-based biodiversity analysis of metaproteome samples. Journal of Proteome Research 11(12), 5773-5780.
Marttinen, P., Tang, J., De Baets B., Dawyndt, P. & Corander, J. (2009). Bayesian clustering of fuzzy feature vectors using a quasi-likelihood approach. IEEE Transactions on Pattern Analysis and Machine Intelligence.
Slabbinck, B., Dawyndt, P., Martens, M., De Vos, P. & De Baets B. (2008). TaxonGap: a visualisation tool for intra- and inter-species variation among individual biomarkers. Bioinformatics 24(6): 866-867.
Dawyndt, P., Vancanneyt, M., De Meyer, H. & Swings, J. (2005). Knowledge Accumulation and Resolution of Data Inconsistencies during the Integration of Microbial Information Sources. IEEE Transactions on Knowledge and Data Engineering 17(8), 1111-1126.