Comparative biosecurity informatics to anticipate invasive species threats

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Invasive species cause billions in economic damages to Australia, but we do not have effective means to identify dangerous species before they arrive and cause harm. This project aims to overcome this challenge using the latest techniques in machine learning combined with genetic, ecological, and functional datasets for thousands of species. This project expects to generate a novel framework that allows us to identify and rank dangerous invasive species in an unbiased way, helping to safeguard Australia's unique biological community. Expected outcomes include improved methods for detecting ecologically and functionally similar species, providing substantial economic efficiency benefits to Australian biosecurity.