Dr. Cathy Westhues, Machine Learning Scientist at Computomics, presented her R package learnMET at the 18th meeting of the EUCARPIA Section Biometrics in Plant Breeding. The conference took place in September on the Paris-Saclay University Campus, France. Cathy presented her work in the session devoted to Gene-by-Environment Interaction and Crop Growth Modeling.
The full title of the presentation was “learnMET: an R package to apply nonlinear algorithms for genomic prediction using multi-environment trial data”. The package lets you input multi-environment breeding datasets (genomic, phenotypic and potentially environmental data), from which it will generate phenotypic predictions—using machine learning techniques. The use of environmental data allows you to connect environments across locations and years to help improve the prediction of genotype performance in new environments.
Cathy had programmed the R package as part of her dissertation, entitled “Investigation of machine learning approaches to predict quantitative traits using environmental and genomic information”, which she successfully defended in May 2022 at University of Göttingen, Germany.
With her progressive and innovative work aligning perfectly with Computomics’ endeavors, we are glad that Cathy chose to work for us. Cathy joined Computomics in May 2022 as a Machine Learning Scientist, further developing and advancing xSeedScore, our machine learning-based technology for predictive breeding. She also works on customer-specific projects related to GxE interactions and is involved in the BMBF-funded project “CropML”, in which Computomics collaborates with the University of Applied Sciences Weihenstephan-Triesdorf and TUM Campus Straubing. We are happy to have her on board!
Dr. Cathy Westhues, Machine Learning Scientist at Computomics
Don’t hesitate to contact Cathy directly if you are interested in knowing more about machine learning-based technologies for predictive breeding!
Cathy worked with public maize and rice datasets. Photo "Rice almost ready for harvest" by Sergio Camalich on Unsplash.