Leveraging genomics and deep learning for biodiversity conservation
Preserving biodiversity is not only an urgent matter for the natural world, but also for long-term human health. As the world undergoes dramatic human-induced change, we need to identify species most at risk of extinction and formulate mitigation tactics. Current risk identification approaches are very time and resource intensive, making them unfeasible for many species. The genome of an organism provides valuable information about its past, present, and future and could be leveraged to rapidly identify whether a species is at risk. Despite this, we currently lack the tools to do this for a wide range of species. Our research program will bring the world of genomics to species without access to high quality samples or funding by developing new approaches to reliably assemble and analyse their genomes. Furthermore, we will take advantage of recent advances in machine learning to provide a rapid and efficient method to predict extinction risk in living species based on their genomes.