Review



punctaspecks graphical user interface (gui)  (MathWorks Inc)


Bioz Verified Symbol MathWorks Inc is a verified supplier  
  • Logo
  • About
  • News
  • Press Release
  • Team
  • Advisors
  • Partners
  • Contact
  • Bioz Stars
  • Bioz vStars
    • 90
      Buy from Supplier

    Structured Review

    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
    Average 90 stars, based on 1 article reviews
    punctaspecks graphical user interface (gui) - by Bioz Stars, 2026-03
    90/100 stars

    Images

    1) Product Images from "PunctaSpecks: A Tool for Automated Detection, Tracking, and Analysis of Multiple Types of Fluorescently Labeled Biomolecules"

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

    Journal: Cell calcium

    doi: 10.1016/j.ceca.2020.102224

    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.
    Figure Legend 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.

    Techniques Used: 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).
    Figure Legend 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).

    Techniques Used:



    Similar Products

    punctaspecks graphical user interface (gui)  (MathWorks Inc)
    90
    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
    Average 90 stars, based on 1 article reviews
    punctaspecks graphical user interface (gui) - 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: