scholarly journals A colorimetric microplate assay method for high-throughput analysis of arginase activity in vitro

2008 ◽  
Vol 383 (2) ◽  
pp. 332-334 ◽  
Author(s):  
Efewmonkiekie W. Iyamu ◽  
Toshio Asakura ◽  
Gerald M. Woods
Keyword(s):  
High Throughput ◽  
Arginase Activity ◽  
Assay Method ◽  
Microplate Assay ◽  
High Throughput Analysis ◽  
Throughput Analysis

scholarly journals An in vitro assay for clonogenic, high‐throughput analysis of intestinal stem cells

2012 ◽  
Vol 26 (S1) ◽  
Author(s):  
Adam David Gracz ◽  
Michael J Johnston ◽  
Fengchao Wang ◽  
Ian A Williamson ◽  
Yuli Wang ◽  
...  
Keyword(s):  
Stem Cells ◽  
High Throughput ◽  
In Vitro Assay ◽  
Intestinal Stem Cells ◽  
High Throughput Analysis ◽  
Vitro Assay ◽  
Throughput Analysis

scholarly journals Fast in vitro protocol for the visualization and quantitative high-throughput analysis of sprouting angiogenesis by confocal microscopy

2021 ◽  
Vol 2 (3) ◽  
pp. 100690
Author(s):  
Lanette Kempers ◽  
Ivo van der Bijl ◽  
Anne-Marieke D. van Stalborch ◽  
Bas Ponsioen ◽  
Coert Margadant
Keyword(s):  
Confocal Microscopy ◽  
High Throughput ◽  
High Throughput Analysis ◽  
Throughput Analysis ◽  
Sprouting Angiogenesis

scholarly journals MyelinJ: an ImageJ macro for high throughput analysis of myelinating cultures

2019 ◽  
Vol 35 (21) ◽  
pp. 4528-4530 ◽  
Author(s):  
Michael J Whitehead ◽  
George A McCanney ◽  
Hugh J Willison ◽  
Susan C Barnett
Keyword(s):  
Statistical Analysis ◽  
High Throughput ◽  
Supplementary Information ◽  
Local Contrast ◽  
High Throughput Analysis ◽  
Throughput Analysis ◽  
Neurite Density ◽  
Supplementary Material ◽  
User Friendly

Abstract Summary MyelinJ is a free user friendly ImageJ macro for high throughput analysis of fluorescent micrographs such as 2D-myelinating cultures and statistical analysis using R. MyelinJ can analyse single images or complex experiments with multiple conditions, where the ggpubr package in R is automatically used for statistical analysis and the production of publication quality graphs. The main outputs are percentage (%) neurite density and % myelination. % neurite density is calculated using the normalize local contrast algorithm, followed by thresholding, to adjust for differences in intensity. For % myelination the myelin sheaths are selected using the Frangi vesselness algorithm, in conjunction with a grey scale morphology filter and the removal of cell bodies using a high intensity mask. MyelinJ uses a simple graphical user interface and user name system for reproducibility and sharing that will be useful to the wider scientific community that study 2D-myelination in vitro. Availability and implementation MyelinJ is freely available at https://github.com/BarnettLab/MyelinJ. For statistical analysis the freely available R and the ggpubr package are also required. MyelinJ has a user guide (Supplementary Material) and has been tested on both Windows (Windows 10) and Mac (High Sierra) operating systems. Supplementary information Supplementary data are available at Bioinformatics online.

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