punctaspecks graphical user interface (gui) Search Results


punctaspecks graphical user interface (gui)  (MathWorks Inc)
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MathWorks Inc punctaspecks graphical user interface (gui)
Various steps used by <t>PunctaSpecks</t> for noise removal and puncta identification. (A) Synthetic movie stack containing dynamical activity of objects under investigation (only 5 frames are shown). (B) Maximum intensity profile (MIP) image of the whole movie. (C) Puncta identified by PunctaSpecks using a given algorithm (Otsu in this case) are encircled on the MIP image to ease the visualization and further adjustment of parameters for accurate detection of all puncta. Histograms of the areas (D), mean fluorescence intensity (E) of all puncta, and (F) mean square displacement as a function of time for the mobile puncta.
Punctaspecks Graphical User Interface (Gui), 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/punctaspecks graphical user interface (gui)/product/MathWorks Inc
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punctaspecks graphical user interface (gui) - by Bioz Stars, 2026-03
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gui for punctaspecks  (MathWorks Inc)
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MathWorks Inc gui for punctaspecks
Various steps used by <t>PunctaSpecks</t> for noise removal and puncta identification. (A) Synthetic movie stack containing dynamical activity of objects under investigation (only 5 frames are shown). (B) Maximum intensity profile (MIP) image of the whole movie. (C) Puncta identified by PunctaSpecks using a given algorithm (Otsu in this case) are encircled on the MIP image to ease the visualization and further adjustment of parameters for accurate detection of all puncta. Histograms of the areas (D), mean fluorescence intensity (E) of all puncta, and (F) mean square displacement as a function of time for the mobile puncta.
Gui For Punctaspecks, 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/gui for punctaspecks/product/MathWorks Inc
Average 90 stars, based on 1 article reviews
gui for punctaspecks - by Bioz Stars, 2026-03
90/100 stars
  Buy from Supplier
punctaspecks  (MathWorks Inc)
90
MathWorks Inc punctaspecks
Various steps used by <t>PunctaSpecks</t> for noise removal and puncta identification. (A) Synthetic movie stack containing dynamical activity of objects under investigation (only 5 frames are shown). (B) Maximum intensity profile (MIP) image of the whole movie. (C) Puncta identified by PunctaSpecks using a given algorithm (Otsu in this case) are encircled on the MIP image to ease the visualization and further adjustment of parameters for accurate detection of all puncta. Histograms of the areas (D), mean fluorescence intensity (E) of all puncta, and (F) mean square displacement as a function of time for the mobile puncta.
Punctaspecks, 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/punctaspecks/product/MathWorks Inc
Average 90 stars, based on 1 article reviews
punctaspecks - by Bioz Stars, 2026-03
90/100 stars
  Buy from Supplier

Image Search Results


Various steps used by PunctaSpecks for noise removal and puncta identification. (A) Synthetic movie stack containing dynamical activity of objects under investigation (only 5 frames are shown). (B) Maximum intensity profile (MIP) image of the whole movie. (C) Puncta identified by PunctaSpecks using a given algorithm (Otsu in this case) are encircled on the MIP image to ease the visualization and further adjustment of parameters for accurate detection of all puncta. Histograms of the areas (D), mean fluorescence intensity (E) of all puncta, and (F) mean square displacement as a function of time for the mobile puncta.

Journal: Cell calcium

Article Title: PunctaSpecks: A Tool for Automated Detection, Tracking, and Analysis of Multiple Types of Fluorescently Labeled Biomolecules

doi: 10.1016/j.ceca.2020.102224

Figure Lengend Snippet: Various steps used by PunctaSpecks for noise removal and puncta identification. (A) Synthetic movie stack containing dynamical activity of objects under investigation (only 5 frames are shown). (B) Maximum intensity profile (MIP) image of the whole movie. (C) Puncta identified by PunctaSpecks using a given algorithm (Otsu in this case) are encircled on the MIP image to ease the visualization and further adjustment of parameters for accurate detection of all puncta. Histograms of the areas (D), mean fluorescence intensity (E) of all puncta, and (F) mean square displacement as a function of time for the mobile puncta.

Article Snippet: Algorithms and Features Incorporated in PunctaSpecks Graphical User Interface (GUI) The MATLAB GUI for PunctaSpecks has multiple tabs, where similar tasks are grouped under the same tab, with various processing steps divided into different categories on each tab.

Techniques: Activity Assay, Fluorescence

Verifying the performance of PunctaSpecks using synthetic data. (A) Frame-by-frame signal to noise ratio of the synthetic data at two different noise levels. Histograms of areas (B), mean open times (log scale) (C), and dwell times (log scale) (D) of all puncta with true (blue) and those from PunctaSpecks at noise levels 25 (green) and 150 (red). (E) Histogram of mean intensities of all puncta with true values (blue) and those from PunctaSpecks at noise level of 25 (green) and 150 (red). The actual trajectory of a sample mobile punctum (blue) and the one identified by PunctaSpecks at noise level of 150 (red) (F).

Journal: Cell calcium

Article Title: PunctaSpecks: A Tool for Automated Detection, Tracking, and Analysis of Multiple Types of Fluorescently Labeled Biomolecules

doi: 10.1016/j.ceca.2020.102224

Figure Lengend Snippet: Verifying the performance of PunctaSpecks using synthetic data. (A) Frame-by-frame signal to noise ratio of the synthetic data at two different noise levels. Histograms of areas (B), mean open times (log scale) (C), and dwell times (log scale) (D) of all puncta with true (blue) and those from PunctaSpecks at noise levels 25 (green) and 150 (red). (E) Histogram of mean intensities of all puncta with true values (blue) and those from PunctaSpecks at noise level of 25 (green) and 150 (red). The actual trajectory of a sample mobile punctum (blue) and the one identified by PunctaSpecks at noise level of 150 (red) (F).

Article Snippet: Algorithms and Features Incorporated in PunctaSpecks Graphical User Interface (GUI) The MATLAB GUI for PunctaSpecks has multiple tabs, where similar tasks are grouped under the same tab, with various processing steps divided into different categories on each tab.

Techniques:

Various steps used by PunctaSpecks for noise removal and puncta identification. (A) Synthetic movie stack containing dynamical activity of objects under investigation (only 5 frames are shown). (B) Maximum intensity profile (MIP) image of the whole movie. (C) Puncta identified by PunctaSpecks using a given algorithm (Otsu in this case) are encircled on the MIP image to ease the visualization and further adjustment of parameters for accurate detection of all puncta. Histograms of the areas (D), mean fluorescence intensity (E) of all puncta, and (F) mean square displacement as a function of time for the mobile puncta.

Journal: Cell calcium

Article Title: PunctaSpecks: A Tool for Automated Detection, Tracking, and Analysis of Multiple Types of Fluorescently Labeled Biomolecules

doi: 10.1016/j.ceca.2020.102224

Figure Lengend Snippet: Various steps used by PunctaSpecks for noise removal and puncta identification. (A) Synthetic movie stack containing dynamical activity of objects under investigation (only 5 frames are shown). (B) Maximum intensity profile (MIP) image of the whole movie. (C) Puncta identified by PunctaSpecks using a given algorithm (Otsu in this case) are encircled on the MIP image to ease the visualization and further adjustment of parameters for accurate detection of all puncta. Histograms of the areas (D), mean fluorescence intensity (E) of all puncta, and (F) mean square displacement as a function of time for the mobile puncta.

Article Snippet: Graphical User Interface (GUI) The MATLAB GUI for PunctaSpecks has multiple tabs, where similar tasks are grouped under the same tab, with various processing steps divided into different categories on each tab.

Techniques: Activity Assay, Fluorescence

Verifying the performance of PunctaSpecks using synthetic data. (A) Frame-by-frame signal to noise ratio of the synthetic data at two different noise levels. Histograms of areas (B), mean open times (log scale) (C), and dwell times (log scale) (D) of all puncta with true (blue) and those from PunctaSpecks at noise levels 25 (green) and 150 (red). (E) Histogram of mean intensities of all puncta with true values (blue) and those from PunctaSpecks at noise level of 25 (green) and 150 (red). The actual trajectory of a sample mobile punctum (blue) and the one identified by PunctaSpecks at noise level of 150 (red) (F).

Journal: Cell calcium

Article Title: PunctaSpecks: A Tool for Automated Detection, Tracking, and Analysis of Multiple Types of Fluorescently Labeled Biomolecules

doi: 10.1016/j.ceca.2020.102224

Figure Lengend Snippet: Verifying the performance of PunctaSpecks using synthetic data. (A) Frame-by-frame signal to noise ratio of the synthetic data at two different noise levels. Histograms of areas (B), mean open times (log scale) (C), and dwell times (log scale) (D) of all puncta with true (blue) and those from PunctaSpecks at noise levels 25 (green) and 150 (red). (E) Histogram of mean intensities of all puncta with true values (blue) and those from PunctaSpecks at noise level of 25 (green) and 150 (red). The actual trajectory of a sample mobile punctum (blue) and the one identified by PunctaSpecks at noise level of 150 (red) (F).

Article Snippet: Graphical User Interface (GUI) The MATLAB GUI for PunctaSpecks has multiple tabs, where similar tasks are grouped under the same tab, with various processing steps divided into different categories on each tab.

Techniques:

Various steps used by PunctaSpecks for noise removal and puncta identification. (A) Synthetic movie stack containing dynamical activity of objects under investigation (only 5 frames are shown). (B) Maximum intensity profile (MIP) image of the whole movie. (C) Puncta identified by PunctaSpecks using a given algorithm (Otsu in this case) are encircled on the MIP image to ease the visualization and further adjustment of parameters for accurate detection of all puncta. Histograms of the areas (D), mean fluorescence intensity (E) of all puncta, and (F) mean square displacement as a function of time for the mobile puncta.

Journal: Cell calcium

Article Title: PunctaSpecks: A Tool for Automated Detection, Tracking, and Analysis of Multiple Types of Fluorescently Labeled Biomolecules

doi: 10.1016/j.ceca.2020.102224

Figure Lengend Snippet: Various steps used by PunctaSpecks for noise removal and puncta identification. (A) Synthetic movie stack containing dynamical activity of objects under investigation (only 5 frames are shown). (B) Maximum intensity profile (MIP) image of the whole movie. (C) Puncta identified by PunctaSpecks using a given algorithm (Otsu in this case) are encircled on the MIP image to ease the visualization and further adjustment of parameters for accurate detection of all puncta. Histograms of the areas (D), mean fluorescence intensity (E) of all puncta, and (F) mean square displacement as a function of time for the mobile puncta.

Article Snippet: We have developed an all-in-one MATLAB-based tool called PunctaSpecks, with a graphical user interface (GUI), that implements algorithms for identifying and characterizing fluorescently labeled objects in time-lapse image stacks.

Techniques: Activity Assay, Fluorescence

Verifying the performance of PunctaSpecks using synthetic data. (A) Frame-by-frame signal to noise ratio of the synthetic data at two different noise levels. Histograms of areas (B), mean open times (log scale) (C), and dwell times (log scale) (D) of all puncta with true (blue) and those from PunctaSpecks at noise levels 25 (green) and 150 (red). (E) Histogram of mean intensities of all puncta with true values (blue) and those from PunctaSpecks at noise level of 25 (green) and 150 (red). The actual trajectory of a sample mobile punctum (blue) and the one identified by PunctaSpecks at noise level of 150 (red) (F).

Journal: Cell calcium

Article Title: PunctaSpecks: A Tool for Automated Detection, Tracking, and Analysis of Multiple Types of Fluorescently Labeled Biomolecules

doi: 10.1016/j.ceca.2020.102224

Figure Lengend Snippet: Verifying the performance of PunctaSpecks using synthetic data. (A) Frame-by-frame signal to noise ratio of the synthetic data at two different noise levels. Histograms of areas (B), mean open times (log scale) (C), and dwell times (log scale) (D) of all puncta with true (blue) and those from PunctaSpecks at noise levels 25 (green) and 150 (red). (E) Histogram of mean intensities of all puncta with true values (blue) and those from PunctaSpecks at noise level of 25 (green) and 150 (red). The actual trajectory of a sample mobile punctum (blue) and the one identified by PunctaSpecks at noise level of 150 (red) (F).

Article Snippet: We have developed an all-in-one MATLAB-based tool called PunctaSpecks, with a graphical user interface (GUI), that implements algorithms for identifying and characterizing fluorescently labeled objects in time-lapse image stacks.

Techniques: