AI-informed conservation genomics

van Oosterhout, Cock ORCID: (2024) AI-informed conservation genomics. Heredity, 132. pp. 1-4. ISSN 0018-067X

[thumbnail of vanOosterhout_2024_Heredity]
PDF (vanOosterhout_2024_Heredity) - Published Version
Available under License Creative Commons Attribution.

Download (1MB) | Preview


Genomic data and Artificial Intelligence (AI) models will start to play an increasingly important role in conservation biology. In a recent study, Wilder et al. (2023) analysed genomic data from 240 mammal species to predict their extinction risk categories in the Red List of the International Union for Conservation of Nature (IUCN). The study processed genomic data with a machine learning model, thereby demonstrating the value of these data for the conservation of biodiversity. Wilder et al. (2023) thus show how reference genomes—and thus, genomic data more broadly—could be used for initial, cost-effective extinction risk assessments, accelerating progress made in the Red List.

Item Type: Article
Additional Information: Funding information: Earth and Life Systems Alliance (ELSA), and the Royal Society International Collaboration Award (2020) (Ref.: ICA\R1\201194).
Uncontrolled Keywords: artificial intelligence (ai),conservation genomics,computer modelling,genetics(clinical),genetics ,/dk/atira/pure/subjectarea/asjc/2700/2716
Faculty \ School: Faculty of Science > School of Environmental Sciences
UEA Research Groups: Faculty of Science > Research Centres > Centre for Ecology, Evolution and Conservation
Related URLs:
Depositing User: LivePure Connector
Date Deposited: 07 May 2024 10:31
Last Modified: 09 May 2024 08:30
DOI: 10.1038/s41437-023-00666-x


Downloads per month over past year

Actions (login required)

View Item View Item