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ZENODO
Dataset . 2023
License: CC BY
Data sources: Datacite
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ZENODO
Dataset . 2023
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Quantification of Giant Unilamellar Vesicle Fusion Products by High-Throughput Image Analysis - Microscopy Data

Authors: Caliari, Adriano; Hanczyc, Martin; Imai, Masayuki; Xu, Jian; Yomo, Tetsuya;

Quantification of Giant Unilamellar Vesicle Fusion Products by High-Throughput Image Analysis - Microscopy Data

Abstract

Microscopy dataset of multipoint-multichannel images of giant unilamellar vesicles (GUVs) suspensions analysed in "Quantification of Giant Unilamellar Vesicle Fusion Products by High-Throughput Image Analysis" (under revision). Three folders concerning different sections of the work are included. "preliminary analysis.zip" contians the raw files and analysis scripts for recall computation and imaging setup optimization as described in the paper. Timelapse data was excluded due to file size restrictions (available upon request at the corresponding authors of the work). "IFC comparison.zip" contains raw files and analysis scripts used to optimize colocalization computation in lipid exchange and content exchange experiments. "GUV fusion analysis" contains raw files and analysis scripts for the quantification of lipid and content exchange upon sodium chloride-induced aggregation. Further details on the analysis are provided in the paper. The R scripts require files saved upon analysis of the raw files by the ImageJ macro "CE_analysis_CPU.ijm" included here. The R environment of the complete analysis are included in each folder to provide easier access to the elaborated data.

{"references": ["https://doi.org/10.3390/ijms24098241"]}

Related Organizations
Keywords

image analysis, Giant Unilamellar Vesicles, high throughput, Vesicle fusion

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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