Fig. 5

a RDF model for each tissue-specific graph: boxes represent classes of entities; a relation between a TF and a gene is characterized by (i) weightP, the score which models the ability of the regulation to be operated through a promoter region, (ii) weightE, the score which models the ability of the regulation to be operated through an enhancer region, (iii) a score composed of the maximum of weightE and weightP, and (iv) the score of the relation given by Regulatory Circuits. At least one of these scores has a non-zero value. b Description of the content of the 394 tissue TF-gene regulatory networks. Each network is represented by an RDF graph based on the RDF model described in (a). The number of TF-gene interactions in the corresponding regulatory network is the number of instances of the “Relation” class in the graph. c Execution times of the queries insert_tissue X.rq where X depends on the number of samples in the tissue (cf. Fig. 3 and github repository) for contructing the graphs in (b), calculated for the first 55 tissues networks. Structure of the 394 tissue-specific graphs representing the parameters of the TF-gene regulation relations