An Earlham Institute team that has developed machine learning technology to find genetic markers for important traits in plants has been awarded £25,000 of funding from UKRI. The funding will support market discovery and skills development for the project, helping to commercialise the BBSRC-funded research.

TraitSeq, developed by Josh Colmer during his PhD at the Earlham Institute, is an end-to-end laboratory and computational pipeline that uses cutting-edge machine learning (ML) methods to generate biomarkers using transcriptomic data. 

These biomarkers have the potential to predict useful physiological, biochemical, or metabolic traits and changes.

The technology is the culmination of Colmer’s involvement in a number of projects during his PhD in the Anthony Hall Group at the Earlham Institute…Read more