Using open data and machine learning approaches to decode the regulatory regions of wheat

The life sciences are becoming increasingly data rich, yet how to best exploit this information remains a challenge and a bottleneck in advancing our understanding. Machine learning (ML) and artificial intelligence (AI) offer new approaches for exploring these datasets and generating testable hypotheses. The methods developed through the project will have direct application to crop breeding and engineering.