FAIR Data Point
RESTful web service that enables data owners to expose their data sets using rich machine-readable metadata.
Prediction of candidate genes for traits using interoperable genome annotations
Food demand is projected to increase by 50% in 2030. One way to tackle this challenge is by breeding new crops to ensure food security; crops, for example, that are more resistant to drought. Genetics research is increasingly focusing on mining genome annotations to identify the genes that are likely to be responsible for specific traits we would like to see improved. Since these annotated genome datasets are growing exponentially, and as humans are unable to quickly and easily convert this data into useful information, an eScience infrastructure will be designed to process all this data effectively and make it insightful.
An open data resource to achieve a synthesis of the evolution and ecology of traits
Open discovery and exchange for all
Chemical informatics for metabolite identification and biochemical network reconstruction
Capitalizing on the growth of scientific knowledge on food
The Virtual Laboratory for Plant Breeding
RESTful web service that enables data owners to expose their data sets using rich machine-readable metadata.
Builds a web API from SPARQL queries hosted on GitHub to accessing triple store data.
Access integrated data on genes and associated traits in plants
Extract gene-trait associations from scientific literature
Make genome annotations semantically interoperable