A visualization approach to analyse bacterial sRNA-mediated regulatory networks
Résumé
Many recent reviews show a wide spectrum of regulatory functions in bacteria where RNAs are involved. Focusing on the sRNAs that interact with mRNAs, the in silico prediction of interactions is still challenging as one of the main difficulty relies on the large proportion of false predictions. Therefore, novel strategies have to be proposed to improve the specificity of computational predictions before selecting a list of prioritized candidates for the experimental validation stage. Based on a network modeling approach, we present rNAV, a visualization software designed to help the identification of pertinent and reasonable sRNA-mRNA pair candidates from a list of thousand target predictions. This software has been applied to the analysis of the sRNA-mediated network of Escherichia coli.