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Fred Van Ex

Fred Van Ex

Fred Van Ex will talk about using deep learning methods to understand wheat genomics data at the IWGSC Standard and Protocols workshop at PAG.

Current position 

Head of Trait Discovery
Bayer CropScience

Research Interest

Artificial Intelligence, Deep Learning, High-throughput phenotyping, Genomics, Epigenomics, Protein Engineering, Gene Editing.

Current Projects

Deep Learning, a specific class of machine learning, is a breakthrough technology in data science that shows great promise to increase the pace of research in biological sciences. Deep Learning algorithms learn meaningful features in large scale and complex biological data sets by finding structure and making accurate predictions. Originally inspired by neural networks, deep learning methods are already successful in image recognition tasks.

Bayer is actively researching applications of Deep Learning methods on diverse sets of complex data such as high throughput images and genomics data in order to accelerate our ability to improve crops. We are currently making rapid progress on the development of deep learning approaches for annotation of high throughput phenotype data of a variety of plant tissues. As a next step, Bayer is preparing to apply Deep Learning approaches on a diverse set of wheat genomics data in order to increase both the speed and accuracy of the functional annotation of the wheat genome.

PAG talk

Tuesday, 16 January 2018, 2:20 pm
Deep Learning Methods for Understanding Wheat Genomics Data


Bayer Crop Science