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Case Study

Build predictive tools to support targeted gene editing to improve crop yield

Support discovery of targets to increase yield and resilience of important, staple food crops using a scalable AI platform.

Challenge

Our agricultural biotech client needed a platform to search the current scientific literature to identify gene targets for desired traits from complex genomic and environmental relationships, based on genome wide association studies (GWAS).

Solution

We helped develop innovative genomic simulation techniques to predict plant traits. We trained NLP models on a large set of published scientific literature to put variant recommendations in the context of global biomedical knowledge, providing scientists with a better understanding of past studies and the competitive landscape.

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