Exposing The Cancer Genome Atlas (TCGA) as a SPARQL endpoint

摘要

Automated discovery of candidate biomarkers from multiple databases has been the central challenge in the Life Sciences in general and in the study of systemic processes such as those documented by The Cancer Genome Atlas (TCGA) in particular. The maturation of Semantic Web technologies offers solutions to those problems by allowing the query to be defined by navigating a normally represented domains of discourse instantiated by the data. We address the systems challenge of The Cancer Genome Atlas initiative (http://cancergenome.nih.gov/), which generates a large scale repository of high throughput molecular biology data generated and processed at 5 academic facilities across the USA.