jyb4444/Reticula_GNN: Application of a metabolic network-based graph neural network for the identification of toxicant-induced perturbations
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| Format: | Recurso digital |
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Zenodo
2025
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| _version_ | 1866902115641720832 |
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| author | Rance Nault jyb4444 |
| author_facet | Rance Nault jyb4444 |
| contents | <p>Our studies illustrate how use of a reaction-based graph neural network can support the discovery of toxicant induced metabolic perturbations, and highlight strengths and challenges in the application of artificial intelligence methods for environmental health research.</p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_15264946 |
| institution | Zenodo |
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| publishDate | 2025 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | jyb4444/Reticula_GNN: Application of a metabolic network-based graph neural network for the identification of toxicant-induced perturbations Rance Nault jyb4444 <p>Our studies illustrate how use of a reaction-based graph neural network can support the discovery of toxicant induced metabolic perturbations, and highlight strengths and challenges in the application of artificial intelligence methods for environmental health research.</p> |
| title | jyb4444/Reticula_GNN: Application of a metabolic network-based graph neural network for the identification of toxicant-induced perturbations |
| url | https://doi.org/10.5281/zenodo.15264946 |