candYgene

An eScience infrastructure for improved plant breeding

Enabling precision breeding

Enabling precision breeding

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.

Image: Pluma (CC License)

eScience Research Engineer Dr. Arnold Kuzniar

In 2015 Arnold joined the Netherlands eScience Center where he works on the application of semantic web technologies on biomedical data integration and knowledge discovery.

Profile page
eScience Research Engineer Dr. Anand Gavai

With his broad interest in understanding data from various domains Anand will work on semantic web framework to understand high dimentional data from scientific articles.

Profile page

Related projects

Sign up for our newsletter