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van Oosterhout, Cock 
ORCID: https://orcid.org/0000-0002-5653-738X
(2024)
AI-informed conservation genomics.
Heredity, 132.
pp. 1-4.
ISSN 0018-067X
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Abstract
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 |
| URI: | https://ueaeprints.uea.ac.uk/id/eprint/95075 |
| DOI: | 10.1038/s41437-023-00666-x |
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