Séminaire virtuel: vendredi 07 avril 2023
Clémence Reda

Lien Zoom

  • Meeting ID: 867 6409 6440
  • passcode: 149120

13h00 - 13h50 – Clémence Réda (Paris)

NORDic: a package for the automated identification of disease-associated Boolean networks and master regulators

The in silico detection of master regulator genes is a popular attempt at speeding up drug development. These genes might be directly related to the onset of the disease, or may act on one pathway which counteracts the associated symptoms. Then, one could perhaps screen drugs to select chemical compounds targeting these genes. In prior works, the detection of these candidates was performed through the identification of the regulatory interactions between genes of interest for the disease. Indeed, system biology approaches have proven a useful tool to integrate transcriptomic data and predict transcriptional profiles under gene perturbations. However, for rare or tropical neglected diseases, building such a regulatory model can become a tedious and time-consuming task. To tackle these issues, we have implemented NORDic, a multi-purpose Python package. First, NORDic allows to build, in a reproducible and transparent fashion, a gene regulatory network using publicly available data. Second, NORDic enables the identification of master regulatory genes, which have a large impact on the dynamics of the gene regulation in a specific disease-related transcriptional context. We applied this approach to temporal lobe epilepsy and major depressive disorder, and were able to recover potentially promising therapeutic targets.

Dernière modification le 07/04/2023