A LOGICAL AND ONTOLOGICAL FRAMEWORK FOR KNOWLEDGE DISCOVERY ON GENE REGULATORY NETWORKS. CASE STUDY: BILE ACID AND XENOB
Dec 2020 - Current (4 years 7 months)
This work aims to develop a novel computational framework for automatic or semi-automatic modeling of gene regulatory networks, in which possible connections between genetic structural knowledge and other forms of knowledge available about GRNs can be explored. To perform the modeling of such networks, we consult computing services available through portals on the Internet. Some of these portals are: GeneOntology, PDB, HGNC, PathwayCommons, UniProt, PubMed, Mesh, among others. The mentioned sites provide services that make possible automatic access and can, therefore, be used to organize knowledge bases that integrate their resources. Our team has developed a prototype system that allows such an integration and the analysis of information s
