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PAM: A Framework for Integrated Analysis of Imaging, Single-Molecule, and Ensemble Fluorescence Data.
Schrimpf, Waldemar; Barth, Anders; Hendrix, Jelle; Lamb, Don C.
Affiliation
  • Schrimpf W; Department of Physical Chemistry, Center for Integrated Protein Science Munich (CIPSM), Nanosystems Initiative Munich (NIM) and Center for Nanoscience (CeNS), Ludwig-Maximilians-Universität, Munich, Germany.
  • Barth A; Department of Physical Chemistry, Center for Integrated Protein Science Munich (CIPSM), Nanosystems Initiative Munich (NIM) and Center for Nanoscience (CeNS), Ludwig-Maximilians-Universität, Munich, Germany.
  • Hendrix J; Dynamic Bioimaging Lab, Biomedical Research Institute (BIOMED), Advanced Optical Microscopy Centre, Faculty of Medicine and Life Sciences, Hasselt University, Diepenbeek, Belgium; Laboratory for Photochemistry and Spectroscopy, Molecular Imaging and Photonics Division, KU Leuven, Heverlee, Belgium.
  • Lamb DC; Department of Physical Chemistry, Center for Integrated Protein Science Munich (CIPSM), Nanosystems Initiative Munich (NIM) and Center for Nanoscience (CeNS), Ludwig-Maximilians-Universität, Munich, Germany. Electronic address: d.lamb@lmu.de.
Biophys J ; 114(7): 1518-1528, 2018 04 10.
Article in En | MEDLINE | ID: mdl-29642023
Fluorescence microscopy and spectroscopy data hold a wealth of information on the investigated molecules, structures, or organisms. Nowadays, the same fluorescence data set can be analyzed in many ways to extract different properties of the measured sample. Yet, doing so remains slow and cumbersome, often requiring incompatible software packages. Here, we present PAM (pulsed interleaved excitation analysis with MATLAB), an open-source software package written in MATLAB that offers a simple and efficient workflow through its graphical user interface. PAM is a framework for integrated and robust analysis of fluorescence ensemble, single-molecule, and imaging data. Although it was originally developed for the analysis of pulsed interleaved excitation experiments, PAM has since been extended to support most types of data collection modalities. It combines a multitude of powerful analysis algorithms, ranging from time- and space-correlation analysis, over single-molecule burst analysis, to lifetime imaging microscopy, while offering intrinsic support for multicolor experiments. We illustrate the key concepts and workflow of the software by discussing data handling and sorting and provide step-by-step descriptions for the individual usage cases.
Subject(s)

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Software / Single Molecule Imaging / Data Analysis / Microscopy, Fluorescence Language: En Journal: Biophys J Year: 2018 Type: Article Affiliation country: Germany

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Software / Single Molecule Imaging / Data Analysis / Microscopy, Fluorescence Language: En Journal: Biophys J Year: 2018 Type: Article Affiliation country: Germany