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RespectM revealed metabolic heterogeneity powers deep learning for reshaping the DBTL cycle
Synthetic biology, relying on Design-Build-Test-Learn (DBTL) cycle, aims to solve medicine, manufacturing, and agriculture problems. However, the DBTL cycle’s Learn (L) step lacks predictive power for the behavior of biological systems, resulting from the incompatibility between sparse testing data...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
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Elsevier
2023
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10329182/ https://www.ncbi.nlm.nih.gov/pubmed/37426353 http://dx.doi.org/10.1016/j.isci.2023.107069 |