Data underlying the publication: Imaging Flow Cytometry for High-Throughput Phenotyping of Synthetic Cells

doi:10.4121/2dc581d0-0237-48dd-b893-1de9f3f47097.v1
The doi above is for this specific version of this dataset, which is currently the latest. Newer versions may be published in the future. For a link that will always point to the latest version, please use
doi: 10.4121/2dc581d0-0237-48dd-b893-1de9f3f47097
Datacite citation style:
Restrepo Sierra, Ana María; Godino, Elisa; Danelon, Christophe (2023): Data underlying the publication: Imaging Flow Cytometry for High-Throughput Phenotyping of Synthetic Cells. Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/2dc581d0-0237-48dd-b893-1de9f3f47097.v1
Other citation styles (APA, Harvard, MLA, Vancouver, Chicago, IEEE) available at Datacite
Dataset

Data underlying the publication: 1. Godino, E., Restrepo Sierra, A. M. & Danelon, C. Imaging Flow Cytometry for High-Throughput Phenotyping of Synthetic Cells. ACS Synth. Biol. 12, 2015–2028 (2023).

The hereby provided research was designed and performed as part of the synthetic biology and BaSyc (NL) consortium efforts to build a synthetic cell from the bottom up. The provided dataset is fraction (100K) of a bigger data set from gene-expressing synthetic vesicles. The data was recorded with The Cytek® Amnis® ImageStream®X Mk II, and analyzed using the IDEAS image analysis software as indicated in the above mentioned publication. Each of the provided files contains the pipeline used for the analysis of the data and can be used as templates for a new analysis. The names of the files indicate the phenotype that was being analyzed, and the figure in the manuscript to which the data belongs to.

history
  • 2023-12-11 first online, published, posted
publisher
4TU.ResearchData
format
.daf files from imaging flow cytometry data
organizations
Delft University of Technology (TU Delft, Faculty of Applied Sciences, Kavli Institute of Nanoscience, Department of Bionanoscience)

DATA

files (8)