matlab-based easyflow Search Results


matlab-based easyflow  (MathWorks Inc)
90
MathWorks Inc matlab-based easyflow
Comparison of currently available software for flow cytometry analysis.
Matlab Based Easyflow, supplied by MathWorks 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/result/matlab-based easyflow/product/MathWorks Inc
Average 90 stars, based on 1 article reviews
matlab-based easyflow - by Bioz Stars, 2026-03
90/100 stars
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python easyflowq  (MathWorks Inc)
90
MathWorks Inc python easyflowq
Comparison of currently available software for flow cytometry analysis.
Python Easyflowq, supplied by MathWorks 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/result/python easyflowq/product/MathWorks Inc
Average 90 stars, based on 1 article reviews
python easyflowq - by Bioz Stars, 2026-03
90/100 stars
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easyflow  (MathWorks Inc)
90
MathWorks Inc easyflow
Screenshots of the <t>EasyFlow</t> (Matlab) (A) and EasyFlowQ (B), with basic functions including managing FCS files, plotting and gating, annotated.
Easyflow, supplied by MathWorks 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/result/easyflow/product/MathWorks Inc
Average 90 stars, based on 1 article reviews
easyflow - by Bioz Stars, 2026-03
90/100 stars
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cytoflex s flow cytometer  (Danaher Inc)
96
Danaher Inc cytoflex s flow cytometer
Screenshots of the <t>EasyFlow</t> (Matlab) (A) and EasyFlowQ (B), with basic functions including managing FCS files, plotting and gating, annotated.
Cytoflex S Flow Cytometer, supplied by Danaher Inc, used in various techniques. Bioz Stars score: 96/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/result/cytoflex s flow cytometer/product/Danaher Inc
Average 96 stars, based on 1 article reviews
cytoflex s flow cytometer - by Bioz Stars, 2026-03
96/100 stars
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easyflow matlab code  (MathWorks Inc)
90
MathWorks Inc easyflow matlab code
Screenshots of the <t>EasyFlow</t> (Matlab) (A) and EasyFlowQ (B), with basic functions including managing FCS files, plotting and gating, annotated.
Easyflow Matlab Code, supplied by MathWorks 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/result/easyflow matlab code/product/MathWorks Inc
Average 90 stars, based on 1 article reviews
easyflow matlab code - by Bioz Stars, 2026-03
90/100 stars
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Image Search Results


Comparison of currently available software for flow cytometry analysis.

Journal: PLOS ONE

Article Title: EasyFlow: An open-source, user-friendly cytometry analyzer with graphic user interface (GUI)

doi: 10.1371/journal.pone.0308873

Figure Lengend Snippet: Comparison of currently available software for flow cytometry analysis.

Article Snippet: Here we present the Matlab-based EasyFlow ( github.com/AntebiLab/easyflow ) and its derivative standalone Python EasyFlowQ ( ym3141.github.io/EasyFlowQ/ ), which are open source user-friendly GUI, can be run on multiple platforms (Windows, MacOS and Linux), and require no coding knowledge.

Techniques: Comparison, Software, Flow Cytometry

Screenshots of the EasyFlow (Matlab) (A) and EasyFlowQ (Python) (B), with basic functions including managing FCS files, plotting and gating, annotated.

Journal: PLOS ONE

Article Title: EasyFlow: An open-source, user-friendly cytometry analyzer with graphic user interface (GUI)

doi: 10.1371/journal.pone.0308873

Figure Lengend Snippet: Screenshots of the EasyFlow (Matlab) (A) and EasyFlowQ (Python) (B), with basic functions including managing FCS files, plotting and gating, annotated.

Article Snippet: Here we present the Matlab-based EasyFlow ( github.com/AntebiLab/easyflow ) and its derivative standalone Python EasyFlowQ ( ym3141.github.io/EasyFlowQ/ ), which are open source user-friendly GUI, can be run on multiple platforms (Windows, MacOS and Linux), and require no coding knowledge.

Techniques:

T cells (Modified Jurkats, see ) were co-cultured with antigen-presenting cells (T2 line, B cells) and their cognate peptide to induce T cell activation. Cells were stained with antibodies to CD19 (B cell marker), CD3 (T cell receptor subunit), and CD69 (T cell activation marker). To gate live cells (A) and single cells (B), cells are plotted using the “Colored Dot Plot’’ option to visualize cell density and identify the sub-populations in the data. Cells are gated using a polygonal 2-dimensional gate, allowing to set the required gate to select for the desired population of cells. Next, a histogram display is used to identify the T cells and remove the B cells (C) and to identify T cells expressing CD3 that can respond to the added peptide (D). Using a 1-dimensional gate, we select the desired cells by choosing the range of values for the corresponding marker within a bi-modal population. In EasyFlow, gates are defined globally so that even if created for a single sample, gates can be applied to all samples in the analysis. In this way, the sequence of gates is applied to all samples in the analysis, enabling the comparison between different conditions. Finally, the percentage of activated cells as determined by the expression of CD69 is examined on the gated live single peptide-sensitive T cells. The percentage of CD69-expressing cells under three conditions: low, high, and no added peptide is examined (E). In all panels, the top row shows the EasyFlow (Matlab) UI, while the bottom row shows the EasyFlowQ (Python) UI.

Journal: PLOS ONE

Article Title: EasyFlow: An open-source, user-friendly cytometry analyzer with graphic user interface (GUI)

doi: 10.1371/journal.pone.0308873

Figure Lengend Snippet: T cells (Modified Jurkats, see ) were co-cultured with antigen-presenting cells (T2 line, B cells) and their cognate peptide to induce T cell activation. Cells were stained with antibodies to CD19 (B cell marker), CD3 (T cell receptor subunit), and CD69 (T cell activation marker). To gate live cells (A) and single cells (B), cells are plotted using the “Colored Dot Plot’’ option to visualize cell density and identify the sub-populations in the data. Cells are gated using a polygonal 2-dimensional gate, allowing to set the required gate to select for the desired population of cells. Next, a histogram display is used to identify the T cells and remove the B cells (C) and to identify T cells expressing CD3 that can respond to the added peptide (D). Using a 1-dimensional gate, we select the desired cells by choosing the range of values for the corresponding marker within a bi-modal population. In EasyFlow, gates are defined globally so that even if created for a single sample, gates can be applied to all samples in the analysis. In this way, the sequence of gates is applied to all samples in the analysis, enabling the comparison between different conditions. Finally, the percentage of activated cells as determined by the expression of CD69 is examined on the gated live single peptide-sensitive T cells. The percentage of CD69-expressing cells under three conditions: low, high, and no added peptide is examined (E). In all panels, the top row shows the EasyFlow (Matlab) UI, while the bottom row shows the EasyFlowQ (Python) UI.

Article Snippet: Here we present the Matlab-based EasyFlow ( github.com/AntebiLab/easyflow ) and its derivative standalone Python EasyFlowQ ( ym3141.github.io/EasyFlowQ/ ), which are open source user-friendly GUI, can be run on multiple platforms (Windows, MacOS and Linux), and require no coding knowledge.

Techniques: Modification, Cell Culture, Activation Assay, Staining, Marker, Expressing, Sequencing, Comparison

Comparison of currently available software for flow cytometry analysis.

Journal: PLOS ONE

Article Title: EasyFlow: An open-source, user-friendly cytometry analyzer with graphic user interface (GUI)

doi: 10.1371/journal.pone.0308873

Figure Lengend Snippet: Comparison of currently available software for flow cytometry analysis.

Article Snippet: Here we present the Matlab-based EasyFlow ( github.com/AntebiLab/easyflow ) and its derivative standalone Python EasyFlowQ ( ym3141.github.io/EasyFlowQ/ ), which are open source user-friendly GUI, can be run on multiple platforms (Windows, MacOS and Linux), and require no coding knowledge.

Techniques: Comparison, Software, Flow Cytometry

Screenshots of the EasyFlow (Matlab) (A) and EasyFlowQ (Python) (B), with basic functions including managing FCS files, plotting and gating, annotated.

Journal: PLOS ONE

Article Title: EasyFlow: An open-source, user-friendly cytometry analyzer with graphic user interface (GUI)

doi: 10.1371/journal.pone.0308873

Figure Lengend Snippet: Screenshots of the EasyFlow (Matlab) (A) and EasyFlowQ (Python) (B), with basic functions including managing FCS files, plotting and gating, annotated.

Article Snippet: Here we present the Matlab-based EasyFlow ( github.com/AntebiLab/easyflow ) and its derivative standalone Python EasyFlowQ ( ym3141.github.io/EasyFlowQ/ ), which are open source user-friendly GUI, can be run on multiple platforms (Windows, MacOS and Linux), and require no coding knowledge.

Techniques:

T cells (Modified Jurkats, see ) were co-cultured with antigen-presenting cells (T2 line, B cells) and their cognate peptide to induce T cell activation. Cells were stained with antibodies to CD19 (B cell marker), CD3 (T cell receptor subunit), and CD69 (T cell activation marker). To gate live cells (A) and single cells (B), cells are plotted using the “Colored Dot Plot’’ option to visualize cell density and identify the sub-populations in the data. Cells are gated using a polygonal 2-dimensional gate, allowing to set the required gate to select for the desired population of cells. Next, a histogram display is used to identify the T cells and remove the B cells (C) and to identify T cells expressing CD3 that can respond to the added peptide (D). Using a 1-dimensional gate, we select the desired cells by choosing the range of values for the corresponding marker within a bi-modal population. In EasyFlow, gates are defined globally so that even if created for a single sample, gates can be applied to all samples in the analysis. In this way, the sequence of gates is applied to all samples in the analysis, enabling the comparison between different conditions. Finally, the percentage of activated cells as determined by the expression of CD69 is examined on the gated live single peptide-sensitive T cells. The percentage of CD69-expressing cells under three conditions: low, high, and no added peptide is examined (E). In all panels, the top row shows the EasyFlow (Matlab) UI, while the bottom row shows the EasyFlowQ (Python) UI.

Journal: PLOS ONE

Article Title: EasyFlow: An open-source, user-friendly cytometry analyzer with graphic user interface (GUI)

doi: 10.1371/journal.pone.0308873

Figure Lengend Snippet: T cells (Modified Jurkats, see ) were co-cultured with antigen-presenting cells (T2 line, B cells) and their cognate peptide to induce T cell activation. Cells were stained with antibodies to CD19 (B cell marker), CD3 (T cell receptor subunit), and CD69 (T cell activation marker). To gate live cells (A) and single cells (B), cells are plotted using the “Colored Dot Plot’’ option to visualize cell density and identify the sub-populations in the data. Cells are gated using a polygonal 2-dimensional gate, allowing to set the required gate to select for the desired population of cells. Next, a histogram display is used to identify the T cells and remove the B cells (C) and to identify T cells expressing CD3 that can respond to the added peptide (D). Using a 1-dimensional gate, we select the desired cells by choosing the range of values for the corresponding marker within a bi-modal population. In EasyFlow, gates are defined globally so that even if created for a single sample, gates can be applied to all samples in the analysis. In this way, the sequence of gates is applied to all samples in the analysis, enabling the comparison between different conditions. Finally, the percentage of activated cells as determined by the expression of CD69 is examined on the gated live single peptide-sensitive T cells. The percentage of CD69-expressing cells under three conditions: low, high, and no added peptide is examined (E). In all panels, the top row shows the EasyFlow (Matlab) UI, while the bottom row shows the EasyFlowQ (Python) UI.

Article Snippet: Here we present the Matlab-based EasyFlow ( github.com/AntebiLab/easyflow ) and its derivative standalone Python EasyFlowQ ( ym3141.github.io/EasyFlowQ/ ), which are open source user-friendly GUI, can be run on multiple platforms (Windows, MacOS and Linux), and require no coding knowledge.

Techniques: Modification, Cell Culture, Activation Assay, Staining, Marker, Expressing, Sequencing, Comparison

Screenshots of the EasyFlow (Matlab) (A) and EasyFlowQ (B), with basic functions including managing FCS files, plotting and gating, annotated.

Journal: bioRxiv

Article Title: EasyFlow: An open source, user friendly cytometry analyzer with graphic user interface (GUI)

doi: 10.1101/2023.08.07.552387

Figure Lengend Snippet: Screenshots of the EasyFlow (Matlab) (A) and EasyFlowQ (B), with basic functions including managing FCS files, plotting and gating, annotated.

Article Snippet: Here we present EasyFlow, an open source flow cytometry analysis GUI based on Matlab or Python, that can be installed and run locally cross-platform-ly (Windows and MacOS), without prerequisite user having previous knowledge on coding.

Techniques: