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Autoencoder neural networks enable low dimensional structure analyses of microbial growth dynamics
The ability to effectively represent microbiome dynamics is a crucial challenge in their quantitative analysis and engineering. By using autoencoder neural networks, we show that microbial growth dynamics can be compressed into low-dimensional representations and reconstructed with high fidelity. Th...
| Autores principales: | , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Nature Publishing Group UK
2023
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10696002/ https://www.ncbi.nlm.nih.gov/pubmed/38049401 http://dx.doi.org/10.1038/s41467-023-43455-0 |