Céline Chevalier (1st year Master bioinformatics) completed in September a 3 months research internship on the construction of a Boolean network for the regulation of Bacilius Subtilis.
The objective was to build both the influence graph and the Boolean rules for the dynamics of the regulatory network of B. Subtilis, which also take into account the links with the metabolism.
The data come from a recent article gathering the knowledge of the state of the art (http://journal.frontiersin.org/article/10.3389/fmicb.2016.00275/full). The interactions are referenced in an excel file.
The student implemented in python a tool which interprets the data in the excel file to extract the influences (activations/inhibitions/unknown) between genes, and deduce some Boolean rules for the activations of the genes of the network.
Various analyses have been conducted on the resulting influence graph and Boolean network. In particular, it turns out that the network, as described in the database, contains very few feedback loop.
The model obtained at the end includes metabolites as input. Therefore, it will allow to compute putative steady states with respect to different metabolic fluxes operating in different stages of the B. Subtilis cell cycle.