Multi-omics integration accurately predicts cellular state in unexplored conditions for Escherichia coli
Multi-omics data integration is a great challenge. Here, the authors compile a database of E. coliproteomics, transcriptomics, metabolomics and fluxomics data to train models of recurrent neural network and constrained regression, enabling prediction of bacterial responses to perturbations.
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| Auteurs principaux: | , , , |
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| Format: | article |
| Langue: | EN |
| Publié: |
Nature Portfolio
2016
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| Sujets: | |
| Accès en ligne: | https://doaj.org/article/99ed3ae0d5e148ff8d397f4572e0ceba |
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