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Broad Institute Inc cellprofiler version 4.0.7
Cellprofiler Version 4.0.7, supplied by Broad Institute Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/cellprofiler+4%2E0%2E7/cellprofiler/pm40499499-73-6-16
Average 90 stars, based on 1 article reviews
cellprofiler version 4.0.7 - by Bioz Stars, 2026-09
90/100 stars

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Article Title: Drebrin Regulates Acetylcholine Receptor Clustering and Organization of Microtubules at the Postsynaptic Machinery.
Article Snippet: For the analysis of the organization of EB3 foci, Ilastik 1.3.3.post3 (European Molecular Biology Laboratory, Heidelberg, Germany) [105] and CellProfiler 4.0.7 (Carpenter Lab, Broad Institute of Harvard and MIT, USA; www.cellprofiler.org) [106] open-source software was used.

Article Title: RAD51 Inhibition Induces R-Loop Formation in Early G1 Phase of the Cell Cycle
Article Snippet: The analysis of acquired images was performed using CellProfiler 4.0.7 (Broad Institute of MIT and Harvard, Cambridge, MA, USA) [ , , ].

Article Title: Spatially visualized single-cell pathology of highly multiplexed protein profiles in health and disease
Article Snippet: After a series of optimizations, cellular segmentation masks and single-cell protein expression data were generated using the Cellprofiler (4.0.7) data analysis pipeline as recommended by Fluidigm.

Software:

Article Title: Development and validation of a radiopathomic model for predicting pathologic complete response to neoadjuvant chemotherapy in breast cancer patients.
Article Snippet: .. We used CellProfiler (version 4.0.7) [21], an opensource image analysis software developed by Broad Institute (Cambridge, Massachusetts), to extract quantitative pathomics features of selected pathological screenshots. ..



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Broad Institute Inc cellprofiler version 4.0.7
Cellprofiler Version 4.0.7, supplied by Broad Institute Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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fluidigm cellprofiler 4.0.7
a Tissue samples were obtained from healthy and diseased tonsils (chronic tonsillitis) in 5-µm-thick formalin-fixed, paraffin-embedded samples. b The thin tissue sections were then stained with metal-conjugated antibodies and get ablated from the tissue’s surface through the argon plasma and analyzed by the time of flight mass spectrometer. c Individual marker images can be assembled and visualized using different colors to observe the marker’s coexpression and spatial organization. d Cells were segmented using <t>CellProfiler</t> software for single-cell quantification. e Single-cell analyses provide the marker expression distributions, including phenotype clustering based on the coexpression of markers. Phenographs of all normal and diseased ROIs show the different phenotypes that make up the sample to n = 25–27 groups. Immune and stromal markers were selected to cluster the entire dataset of the normal and diseased tonsil. The markers list includes CD20, CD68, CD3, CD4, CD8a, granzyme B, pankeratin, and E-cadherin. Created in Biorender.com.
Cellprofiler 4.0.7, supplied by fluidigm, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/cellprofiler+4%2E0%2E7/cellprofiler+4+0+7/pmc08160218-285-17-25
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cellprofiler 4.0.7 - by Bioz Stars, 2026-09
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a Tissue samples were obtained from healthy and diseased tonsils (chronic tonsillitis) in 5-µm-thick formalin-fixed, paraffin-embedded samples. b The thin tissue sections were then stained with metal-conjugated antibodies and get ablated from the tissue’s surface through the argon plasma and analyzed by the time of flight mass spectrometer. c Individual marker images can be assembled and visualized using different colors to observe the marker’s coexpression and spatial organization. d Cells were segmented using CellProfiler software for single-cell quantification. e Single-cell analyses provide the marker expression distributions, including phenotype clustering based on the coexpression of markers. Phenographs of all normal and diseased ROIs show the different phenotypes that make up the sample to n = 25–27 groups. Immune and stromal markers were selected to cluster the entire dataset of the normal and diseased tonsil. The markers list includes CD20, CD68, CD3, CD4, CD8a, granzyme B, pankeratin, and E-cadherin. Created in Biorender.com.

Journal: Communications Biology

Article Title: Spatially visualized single-cell pathology of highly multiplexed protein profiles in health and disease

doi: 10.1038/s42003-021-02166-2

Figure Lengend Snippet: a Tissue samples were obtained from healthy and diseased tonsils (chronic tonsillitis) in 5-µm-thick formalin-fixed, paraffin-embedded samples. b The thin tissue sections were then stained with metal-conjugated antibodies and get ablated from the tissue’s surface through the argon plasma and analyzed by the time of flight mass spectrometer. c Individual marker images can be assembled and visualized using different colors to observe the marker’s coexpression and spatial organization. d Cells were segmented using CellProfiler software for single-cell quantification. e Single-cell analyses provide the marker expression distributions, including phenotype clustering based on the coexpression of markers. Phenographs of all normal and diseased ROIs show the different phenotypes that make up the sample to n = 25–27 groups. Immune and stromal markers were selected to cluster the entire dataset of the normal and diseased tonsil. The markers list includes CD20, CD68, CD3, CD4, CD8a, granzyme B, pankeratin, and E-cadherin. Created in Biorender.com.

Article Snippet: After a series of optimizations, cellular segmentation masks and single-cell protein expression data were generated using the Cellprofiler (4.0.7) data analysis pipeline as recommended by Fluidigm.

Techniques: Formalin-fixed Paraffin-Embedded, Staining, Clinical Proteomics, Mass Spectrometry, Marker, Software, Expressing