High-dimensional data analysis

The group involved in high-dimensional data analysis uses gene ontology for analyzing gene expression data; develops and validates prediction models based on high dimensional regression models; and develops new methods for high dimensional hypothesis testing and multiple testing.


The group is involved in several projects in clinical proteomics, longitudinal data analysis and other complex data structures.


Our group carries out research in a variety of topics,  which are closely related to our involvement in consultation for LUMC studies.

Our Team members

  • Prof. dr. Jelle Goeman, Analysis of high-dimensional medical data
  • Dr. Roula Tsonaka, assistant professor
  • Dr. Mar Rodriguez, assistant professor
  • Dr. Bart Mertens, associate professor
  • Dr. Stefan Böhringer, assistant professor
  • Dr. Szymon Kielbasa, assistant professor