Matches in SemOpenAlex for { <https://semopenalex.org/work/W2992151120> ?p ?o ?g. }
- W2992151120 endingPage "33" @default.
- W2992151120 startingPage "26" @default.
- W2992151120 abstract "Our understanding of the microbial cell is based on averaged values from bulks. Microfluidic single-cell analysis holds the promise of understanding cellular processes from a single cell perspective. But what is needed to measure single-cell physiology and to disclose the consequences of individuality for biotechnology? Current single-cell research is not yet able to provide all the necessary insights, but innovative approaches now emerge that propel the field towards a better understanding of cellular processes via quantitative physiology. Here, we critically review novel single-cell technologies that enable us to control cellular input parameters such as environmental conditions and to measure intracellular processes, as well as novel approaches that enable for the first time to quantify non-averaged cell-specific rates and yields. Finally, we demonstrate how integrating microfluidic single-cell analysis into established population-based experimental workflows might unlock its full potential for biotechnology research in the future." @default.
- W2992151120 created "2019-12-13" @default.
- W2992151120 creator A5061467562 @default.
- W2992151120 creator A5075437632 @default.
- W2992151120 date "2020-06-01" @default.
- W2992151120 modified "2023-10-16" @default.
- W2992151120 title "Microfluidic single-cell analysis in biotechnology: from monitoring towards understanding" @default.
- W2992151120 cites W1567520642 @default.
- W2992151120 cites W1652052270 @default.
- W2992151120 cites W1897231799 @default.
- W2992151120 cites W1977568111 @default.
- W2992151120 cites W1982759742 @default.
- W2992151120 cites W1995118043 @default.
- W2992151120 cites W1996666978 @default.
- W2992151120 cites W2040391983 @default.
- W2992151120 cites W2043471792 @default.
- W2992151120 cites W2058462185 @default.
- W2992151120 cites W2075762672 @default.
- W2992151120 cites W2106411386 @default.
- W2992151120 cites W2109171263 @default.
- W2992151120 cites W2109242001 @default.
- W2992151120 cites W2135461398 @default.
- W2992151120 cites W2150660948 @default.
- W2992151120 cites W2152152614 @default.
- W2992151120 cites W2170133970 @default.
- W2992151120 cites W2171781943 @default.
- W2992151120 cites W2172612097 @default.
- W2992151120 cites W2268716078 @default.
- W2992151120 cites W2515708361 @default.
- W2992151120 cites W2527029076 @default.
- W2992151120 cites W2605256394 @default.
- W2992151120 cites W2626881661 @default.
- W2992151120 cites W2723535088 @default.
- W2992151120 cites W2751932188 @default.
- W2992151120 cites W2757658034 @default.
- W2992151120 cites W2783665855 @default.
- W2992151120 cites W2788041777 @default.
- W2992151120 cites W2791040535 @default.
- W2992151120 cites W2792214402 @default.
- W2992151120 cites W2795129411 @default.
- W2992151120 cites W2798012109 @default.
- W2992151120 cites W2810878055 @default.
- W2992151120 cites W2884966600 @default.
- W2992151120 cites W2890247752 @default.
- W2992151120 cites W2897589467 @default.
- W2992151120 cites W2902798368 @default.
- W2992151120 cites W2902873162 @default.
- W2992151120 cites W2905590181 @default.
- W2992151120 cites W2911925649 @default.
- W2992151120 cites W2915338207 @default.
- W2992151120 cites W2922039477 @default.
- W2992151120 cites W2936869990 @default.
- W2992151120 cites W2944475826 @default.
- W2992151120 cites W2944621097 @default.
- W2992151120 cites W2951525168 @default.
- W2992151120 doi "https://doi.org/10.1016/j.copbio.2019.11.001" @default.
- W2992151120 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/31809975" @default.
- W2992151120 hasPublicationYear "2020" @default.
- W2992151120 type Work @default.
- W2992151120 sameAs 2992151120 @default.
- W2992151120 citedByCount "41" @default.
- W2992151120 countsByYear W29921511202020 @default.
- W2992151120 countsByYear W29921511202021 @default.
- W2992151120 countsByYear W29921511202022 @default.
- W2992151120 countsByYear W29921511202023 @default.
- W2992151120 crossrefType "journal-article" @default.
- W2992151120 hasAuthorship W2992151120A5061467562 @default.
- W2992151120 hasAuthorship W2992151120A5075437632 @default.
- W2992151120 hasConcept C127413603 @default.
- W2992151120 hasConcept C1491633281 @default.
- W2992151120 hasConcept C150903083 @default.
- W2992151120 hasConcept C171250308 @default.
- W2992151120 hasConcept C177212765 @default.
- W2992151120 hasConcept C183696295 @default.
- W2992151120 hasConcept C192562407 @default.
- W2992151120 hasConcept C2776950831 @default.
- W2992151120 hasConcept C2908647359 @default.
- W2992151120 hasConcept C41008148 @default.
- W2992151120 hasConcept C54355233 @default.
- W2992151120 hasConcept C70721500 @default.
- W2992151120 hasConcept C71924100 @default.
- W2992151120 hasConcept C77088390 @default.
- W2992151120 hasConcept C8673954 @default.
- W2992151120 hasConcept C86803240 @default.
- W2992151120 hasConcept C99454951 @default.
- W2992151120 hasConceptScore W2992151120C127413603 @default.
- W2992151120 hasConceptScore W2992151120C1491633281 @default.
- W2992151120 hasConceptScore W2992151120C150903083 @default.
- W2992151120 hasConceptScore W2992151120C171250308 @default.
- W2992151120 hasConceptScore W2992151120C177212765 @default.
- W2992151120 hasConceptScore W2992151120C183696295 @default.
- W2992151120 hasConceptScore W2992151120C192562407 @default.
- W2992151120 hasConceptScore W2992151120C2776950831 @default.
- W2992151120 hasConceptScore W2992151120C2908647359 @default.
- W2992151120 hasConceptScore W2992151120C41008148 @default.
- W2992151120 hasConceptScore W2992151120C54355233 @default.
- W2992151120 hasConceptScore W2992151120C70721500 @default.
- W2992151120 hasConceptScore W2992151120C71924100 @default.