candYgene: enabling precision breeding through FAIR Data

A. Kuzniar, A.K. Gavai, L.O. Ridder, L.O. Bonino da Silva Santos, G. Singh, R.G.F. Visser, H.J. Finkers

Research output: Contribution to conferenceAbstract

Abstract

Genetics research is focusing more and more on mining fully sequenced genomes and their annotations to identify the causal genes associated with specific traits (phenotypes) of interest. However, a complex trait is typically associated with multiple quantitative trait loci (QTLs), each with hundreds of genes positively/negatively affecting the desired trait(s). Our aim is to develop a Big data analytics & semantic interoperability infrastructure for candidate gene prioritization that will aid breeders in the design of an optimal genotype with a desired trait(s) for a given environment.
Original languageEnglish
DOIs
Publication statusPublished - 2015

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