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...

Descripción completa

Detalles Bibliográficos
Autores principales: Meng, Xuanlin, Xu, Ping, Tao, Fei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Article
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

Internet

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

Ejemplares similares