Backup mandate Research Council: Prioritization of variant combinations and detection of oligogenic signatures in epilepsy patients exomes.

Project Details


With the advent of the new sequencing technologies, tremendous progress has been made in understanding the relationship between genotypes and phenotypes. Advances in related computational methods have enabled the development of different prioritization methods that allow to accurately identify in Whole-Exome Sequencing (WES) data which genetic variants are responsible for particular disease phenotypes. However, it was observed that different genetic diseases may be caused by the interaction of different variants in a small number of genes. New prioritization methods are thus necessary because current technology cannot uncover the genetic basis of such diseases. In this project we therefore wish to develop a Prioritization method specifically for variant combinations that is based on intelligent learning solutions
already developed in our group. This method will be evaluated based on the exome data from patients with epilepsy - a disease of poorly understood genetic etiology - to identify potentially meaningful oligogenic signatures. These will be obtained by creating prioritized networks of the gene and variant combinations and should shed new light on the genetic architecture underlying epilepsy. Ultimately, our method will lead to an improved treatment of the disease through precision medicine.
Effective start/end date1/11/211/01/22


  • precision medicine
  • oligogenicity
  • epilepsy
  • machine learning

Flemish discipline codes

  • Analysis of next-generation sequence data
  • Bioinformatics of disease
  • Computational biomodelling and machine learning
  • Development of bioinformatics software, tools and databases
  • Quantitative genetics