Projects per year
My research concerns developing statistical methods for new research designs and new data formats in biomedical science. In particular I focus on omics and big data in general. For integrating omics data I am working on high dimensional multivariate models such as canonical correlation and redundancy analysis and partial least squares methods in general. I developed several software tools that are capable of integrating multiple datasets, each consisting of hundredthousands of variables. Another line of research is focused on using existing registry data for epidemiological cohort studies that are performed in the AMC. I developed methods to jointly perform multiple record linkage and association analyses that are truly unbiased even if the record linkage is done with relatively low quality link variables. This is truly big data analysis because my tools are capable of linking/analyzing datasets covering the entire Dutch population. Both the omics and the linked record data analysis tools are based on parallel computing and make use of clustercomputers, GPU computing and the Dutch grid of computing facilities. Related research subject are related to developing dynamic (prediction) models and causal effects analysis. In addition to these methodological subjects I am co-initiator and co-PI of the HELIUS cohort study of about 25,000 inhabitants of Amsterdam.
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van Altena, A., Aufiero, S., van Barreveld, M., Csala, A., Datema, M., Gras, L., den Hartog, A., van den Hengel, R., van Iperen, E., Khan, H., Luirink, I., Ouwerkerk, W., Ramos, L., Snoeker, B., Vink, P., Wang, J., van Werkhoven, E., Zwinderman, K., Geskus, R. & Tanck, M.
1/06/2012 → …
Development and validation of multivariable models to predict mortality and hospitalization in patients with heart failureVoors, A. A., Ouwerkerk, W., Zannad, F., van Veldhuisen, D. J., Samani, N. J., Ponikowski, P., Ng, L. L., Metra, M., ter Maaten, J. M., Lang, C. C., Hillege, H. L., van der Harst, P., Filippatos, G., Dickstein, K., Cleland, J. G., Anker, S. D. & Zwinderman, A. H., 2017, In: European journal of heart failure. 19, 5, p. 627-634
Research output: Contribution to journal › Article › Academic › peer-review161 Citations (Scopus)
van Iperen, E. P. A., Hovingh, G. K., Asselbergs, F. W. & Zwinderman, A. H., 2017, In: PLOS ONE. 12, 2, e0172082.
Research output: Contribution to journal › Article › Academic › peer-review5 Citations (Scopus)
Dynamic prediction of recurrent events data by landmarking with application to a follow-up study of patients after kidney transplantMusoro, J. Z., Struijk, G. H., Geskus, R. B., ten Berge, I. & Zwinderman, A. H., 2018, In: Statistical methods in medical research. 27, 3, p. 832-845
Research output: Contribution to journal › Article › Academic › peer-review11 Citations (Scopus)
Hof, M. H. P. & Zwinderman, A. H., 2015, In: Statistics in medicine. 34, 1, p. 74-92
Research output: Contribution to journal › Article › Academic › peer-review8 Citations (Scopus)
Correlating multiple SNPs and multiple disease phenotypes: Penalized nonlinear canonical correlation analysisWaaijenborg, S. & Zwinderman, A. H., 2009, In: Bioinformatics (Oxford, England). 25, 21, p. 2764-2771
Research output: Contribution to journal › Article › Academic › peer-review13 Citations (Scopus)