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Related Concept Videos

Protein Dynamics in Living Cells01:19

Protein Dynamics in Living Cells

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Different fluorescence-based techniques are used to study the protein dynamics in living cells. These techniques include FRAP, FRET, and PET.
Fluorescent recovery after photobleaching (FRAP) is a fluorescent-protein-based detection technique used to quantify protein movement rates within the cell. This method exposes a small portion of the cell to an intense laser beam. The laser beam causes permanent photobleaching of the fluorophore-tagged proteins in the exposed region. As the bleached...
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Related Experiment Video

Updated: Jun 13, 2025

Open Source High Content Analysis Utilizing Automated Fluorescence Lifetime Imaging Microscopy
09:30

Open Source High Content Analysis Utilizing Automated Fluorescence Lifetime Imaging Microscopy

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AlliGator: Open Source Fluorescence Lifetime Imaging Analysis in G.

X Michalet1

  • 1Department of Chemistry & Biochemistry, University of California at Los Angeles, 607 Charles E. Young Drive E, Los Angeles, CA 90095.

Biorxiv : the Preprint Server for Biology
|June 12, 2025
PubMed
Summary
This summary is machine-generated.

AlliGator is a new open-source software for Fluorescence Lifetime Imaging (FLI) analysis. It offers a user-friendly interface for complex FLI data processing, including model fitting and phasor analysis.

Keywords:
LabVIEWNLSFPythonfluorescence lifetime imagingphasor analysis

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Area of Science:

  • Biophysics
  • Optical Imaging
  • Data Analysis Software

Background:

  • Fluorescence Lifetime Imaging (FLI) captures temporal fluorescence decay at each image pixel.
  • Analyzing FLI data typically involves complex model fitting or phasor analysis.
  • Existing software packages may lack user-friendliness or comprehensive features.

Purpose of the Study:

  • Introduce AlliGator, an open-source software for Fluorescence Lifetime Imaging (FLI) data analysis.
  • Provide a user-friendly graphical interface (GUI) for advanced FLI analysis techniques.
  • Offer unique features and support for custom plugins to enhance FLI research.

Main Methods:

  • Developed AlliGator using LabVIEW graphical programming language for intuitive GUI design.
  • Implemented established FLI analysis methods: nonlinear least-square fit, maximum likelihood estimation, and phasor analysis.
  • Integrated support for user-developed plugins written in Python for extended functionality.

Main Results:

  • AlliGator provides a comprehensive and accessible platform for FLI data analysis.
  • The software integrates multiple analysis approaches within a single, user-friendly GUI.
  • Unique features and Python plugin support enhance its versatility for researchers.

Conclusions:

  • AlliGator offers a powerful, open-source solution for Fluorescence Lifetime Imaging analysis.
  • Its user-friendly interface and extensible design facilitate broader adoption and application in scientific research.
  • The software empowers researchers to extract more information from FLI datasets.