Computational systems biology
Developing predictive models for precision medicine - overview

With the advances of high-throughput experimental techniques, biomedical research is turning into information science. This requires the use of machine and deep-learning approaches, statistics and mathematical modelling. Individual cellular processes that comprise the interplay of several molecular players, such as cell signaling, can now be quantitatively characterized to allow a systematic view of biological processes. A better understanding of biological processes is crucial in order to provide robust predictive models that improve disease prognoses and treatment strategies.

Our group is exploiting a large variety of data — multi-omics datasets, single-cell proteomics and mass spectrometry-based quantitative proteomics — to dissect the molecular mechanisms of cancer. Our goal is to develop predictive models for precision medicine.