Journal: bioRxiv

Article Title: NetPyNE: a tool for data-driven multiscale modeling of brain circuits

doi: 10.1101/461137

Figure Lengend Snippet: NetPyNE GUI showing 3D representation of M1 network (background), raster plot and population firing rate statistics (top left), voltage traces (bottom left) and firing rate power spectral density (top right).

Article Snippet: The tool’s GUI is available at https://github.com/MetaCell/NetPyNE-UI and is under active development.

Techniques:

Journal: Current protocols in cytometry

Article Title: Generating Quantitative Cell Identity Labels with Marker Enrichment Modeling (MEM)

doi: 10.1002/cpcy.34

Figure Lengend Snippet: Small heatmaps can be displayed in the R GUI Plots panel. Here the output is shown from build.heatmaps() in RStudio.

Article Snippet: It is therefore best practice to set newWindow.heatmaps = TRUE unless the dataset contains approximately ten populations or fewer. fig ft0 fig mode=article f1 fig/graphic|fig/alternatives/graphic mode="anchored" m1 Open in a separate window Figure 2 caption a7 caption a8 View output of build.heatmaps() in the RStudio GUI Small heatmaps can be displayed in the R GUI Plots panel.

Techniques:

Journal: Current protocols in cytometry

Article Title: Generating Quantitative Cell Identity Labels with Marker Enrichment Modeling (MEM)

doi: 10.1002/cpcy.34

Figure Lengend Snippet: Heatmaps are shown in new windows when newWindow.heatmaps = TRUE. Output is shown resulting from setting cluster.MEM = “both.” These plots can be saved as PDF files from the dropdown menu in the window’s File tab.

Article Snippet: It is therefore best practice to set newWindow.heatmaps = TRUE unless the dataset contains approximately ten populations or fewer. fig ft0 fig mode=article f1 fig/graphic|fig/alternatives/graphic mode="anchored" m1 Open in a separate window Figure 2 caption a7 caption a8 View output of build.heatmaps() in the RStudio GUI Small heatmaps can be displayed in the R GUI Plots panel.

Techniques:

Journal: Current protocols in cytometry

Article Title: Generating Quantitative Cell Identity Labels with Marker Enrichment Modeling (MEM)

doi: 10.1002/cpcy.34

Figure Lengend Snippet: Build.heatmaps() creates a new folder called output files as a subdirectory of the working directory and writes output as tab-delimited text files. The files include 1) the population MEM labels (enrichment score row names) that are displayed in the MEM_matrix heatmap, 2) the matrix of population median values, and 3) the matrix of MEM scores.

Article Snippet: It is therefore best practice to set newWindow.heatmaps = TRUE unless the dataset contains approximately ten populations or fewer. fig ft0 fig mode=article f1 fig/graphic|fig/alternatives/graphic mode="anchored" m1 Open in a separate window Figure 2 caption a7 caption a8 View output of build.heatmaps() in the RStudio GUI Small heatmaps can be displayed in the R GUI Plots panel.

Techniques:

Journal: Current protocols in cytometry

Article Title: Generating Quantitative Cell Identity Labels with Marker Enrichment Modeling (MEM)

doi: 10.1002/cpcy.34

Figure Lengend Snippet: View of the output files folder, located in your working directory, after running build.heatmaps() with the argument output.files=TRUE. If you are unsure of where this folder is located, run the command getwd() at the R command line, and the path to your working directory will print to the console.

Article Snippet: It is therefore best practice to set newWindow.heatmaps = TRUE unless the dataset contains approximately ten populations or fewer. fig ft0 fig mode=article f1 fig/graphic|fig/alternatives/graphic mode="anchored" m1 Open in a separate window Figure 2 caption a7 caption a8 View output of build.heatmaps() in the RStudio GUI Small heatmaps can be displayed in the R GUI Plots panel.

Techniques:

Journal: BMC Bioinformatics

Article Title: FoCo: a simple and robust quantification algorithm of nuclear foci

doi: 10.1186/s12859-015-0816-5

Figure Lengend Snippet: Results of automatic γH2AX foci quantification for images of MRC-5 cells from confocal laser-scanning microscope. Quantifications were performed in ImageJ, CellProfiler and FoCo. Image analysis of cells after 10 Gy irradiation ( a ) after 2.5 Gy irradiation ( b ) and control non-irradiated cells ( c ). Dots designate mean foci number per nucleus for considered time points after experiment start. Error bars designate standard error of the mean (SEM) ( n ≥ 100)

Article Snippet: Additionally, GUI FoCo is publicly available at https://sourceforge.net/projects/focicount along with the source code and user documentation.

Techniques: Laser-Scanning Microscopy, Irradiation, Control

Journal: BMC Bioinformatics

Article Title: FoCo: a simple and robust quantification algorithm of nuclear foci

doi: 10.1186/s12859-015-0816-5

Figure Lengend Snippet: Simulation of artificial foci images with pre-defined number of foci. a Foci image of a cell 1 h after 10 Gy irradiation. b Foci image of a non-irradiated cell. c Representative simulated foci image with 62 foci (Irradiated in panel ( e )). d Representative simulated foci image with 6 foci (Control in panel ( e )). e Comparison between pre-defined foci numbers and automatic quantification results. The closer RelDiff 1 to 0, the more precise are the quantification result obtained by the automatic method. f – h Demonstration of quantification results in FoCo, CellProfiler and ImageJ, respectively, applied to the representative image in panel C. i – k Demonstration of quantification results in FoCo, CellProfiler and ImageJ applied to the representative image in panel ( d ), respectively. Red frames, boundaries and circles designate detected foci in FoCo, CellProfiler and ImageJ, respectively. White arrows designate representative foci, which were either not split by the software or wrongly detected

Article Snippet: Additionally, GUI FoCo is publicly available at https://sourceforge.net/projects/focicount along with the source code and user documentation.

Techniques: Irradiation, Control, Comparison, Software

Journal: BMC Bioinformatics

Article Title: FoCo: a simple and robust quantification algorithm of nuclear foci

doi: 10.1186/s12859-015-0816-5

Figure Lengend Snippet: Analysis of images with artificial out-of-focus background signal. a Representative nuclei from base und neighbour images of cells 1 and 6 h after 10 Gy IR and corresponding base images with additional artificial out-of-focus background signal for two different strengths of blur-effect ( f = 1, 6). b Relative differences RelDiff 2 for images of cells 1 and 6 h after 10 Gy IR. Quantifications were performed in ImageJ, CellProfiler and FoCo. The lower RelDiff 2 , the more robust is the method in sense of suppressing out-of-focus background signal

Article Snippet: Additionally, GUI FoCo is publicly available at https://sourceforge.net/projects/focicount along with the source code and user documentation.

Techniques:

Journal: BMC Bioinformatics

Article Title: FoCo: a simple and robust quantification algorithm of nuclear foci

doi: 10.1186/s12859-015-0816-5

Figure Lengend Snippet: γH2AX foci quantifications in FoCo for images from confocal laser-scanning and wide-field fluorescent microscopes. Quantifications were performed for images of MRC-5 cells non-irradiated and after 10 Gy irradiation. Dots designate mean foci number per nucleus for considered time points after experiment start. Error bars designate standard error of the mean (SEM) ( n ≥ 100)

Article Snippet: Additionally, GUI FoCo is publicly available at https://sourceforge.net/projects/focicount along with the source code and user documentation.

Techniques: Irradiation