Computational Biomedicine

We work on a variety of biostatistical and machine learning methods applied to biomedicine, to retrieve insights in the aetiology of complex diseases. For this, we explore CRISPR screens, drug high-throughput screens and clinical patient data, which is typically complemented with multi-omic’s characterisations of the given model organisms. Our research interest is computational early drug discovery including but not limited to drug target identifications, drug repositioning and patient stratifications for personalised medicine.

 

 

 

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