PAM: A Framework for Integrated Analysis of Imaging, Single-Molecule, and Ensemble Fluorescence Data

Area of Science:

• Biophysics
• Spectroscopy
• Microscopy
• Computational Biology

Background:

• Fluorescence microscopy and spectroscopy generate rich data for molecular, structural, and organismal studies.
• Analyzing diverse fluorescence data often requires multiple, incompatible software packages, leading to inefficiency.
• Current analysis methods can be slow and cumbersome, hindering rapid data interpretation.

Purpose of the Study:

• To introduce PAM (pulsed interleaved excitation analysis), an open-source MATLAB software package.
• To provide a unified and efficient workflow for analyzing various types of fluorescence data.
• To support ensemble, single-molecule, and imaging fluorescence data analysis through an integrated framework.

Main Methods:

• Development of PAM, a MATLAB-based software with a graphical user interface.
• Integration of diverse analysis algorithms including correlation analysis, single-molecule burst analysis, and lifetime imaging microscopy.
• Support for multicolor experiments and various data collection modalities beyond pulsed interleaved excitation.

Main Results:

• PAM offers a simple, efficient, and integrated workflow for fluorescence data analysis.
• The software supports a wide range of analysis techniques and data types.
• PAM facilitates robust analysis of ensemble, single-molecule, and imaging fluorescence data.

Conclusions:

• PAM provides a powerful, open-source solution for comprehensive fluorescence data analysis.
• The software enhances accessibility and efficiency for researchers working with fluorescence data.
• PAM streamlines complex analyses, enabling deeper insights from fluorescence experiments.