Wessel N. van Wieringen
Many molecular entities contribute to the working of the cell. How, when, and which of these entities contribute to which cellular processes is not fully understood. In particular, most of these processes are dysregulated in diseases like cancer. Omics data provide (partial) information on (aspects of) the molecular entities present in the cell. To deduce from these data biological tangible conclusions w.r.t. the (dys)functioning of the cell is the challenge I work on. This requires a.o. 1) the formulation of multivariate statistical models (e.g. graphical models) describing cellular processes, 2) the estimation of model parameters from the (high-dimensional) data, 3) understanding the models' limitations in their capacity to explain observed data from dysregulated processes, and 4) re-iterating the previous three steps to improve the models.
Van Wieringen, W.N., Peeters, C.F.W. (2015), "Ridge estimation of inverse covariance matrices from high-dimensional data", arXiv:1403.0904 [stat.ME].
Van Wieringen, W.N., Van der Vaart, A.W. (2015), "Transcriptomic heterogeneity in cancer as a consequence of dysregulation of the gene-gene interaction network", Bulletin of Mathematical Biology, 77(9), 1768-1786.