Towards a Linked Open Data Model for Coffee Functional Relationships

Abstract

The development of technologies for massively disclose genetic information stored within cells generated the genomics revolution, where everyday exponentially growing databases with the description of the chemical structure of novel genes obtained with the automated nucleic acid sequencing. Each of these sequences is necessary to assign a function, in a process known as gene annotation comparing information of unknown sequence with sequences previously studied in the laboratory. This will identify candidate genes associated with traits of interest such as disease susceptibility or resistance, adaptation to the environment or animal or plant production. Given the volume of information, it is necessary that this be presented in a structured way so that such comparisons can be performed by computer agents quickly and it is open to the possibility of generating new knowledge by finding features and novel relationships between genes. This paper aims to present a bioinformatic application for functional relations search of transcriptome for coffee genetic material provided by the Coffee Investigation Center (CENICAFE), using the Bio2RDF biological database, applying new standards for LOD (Linked Open data) necessary to communicate effectively with other reference databases already operating under the scheme or Semantic Web.