PyFDAP: automated analysis of fluorescence decay after photoconversion (FDAP) experiments

Alexander Bläßle; Patrick Müller

doi:10.1093/bioinformatics/btu735

PyFDAP: automated analysis of fluorescence decay after photoconversion (FDAP) experiments

Bioinformatics. 2015 Mar 15;31(6):972-4. doi: 10.1093/bioinformatics/btu735. Epub 2014 Nov 6.

Authors

Alexander Bläßle¹, Patrick Müller¹

Affiliation

¹ Systems Biology of Development Group, Friedrich Miescher Laboratory of the Max Planck Society, 72076 Tübingen, Germany.

PMID: 25380959
DOI: 10.1093/bioinformatics/btu735

Abstract

We developed the graphical user interface PyFDAP for the fitting of linear and non-linear decay functions to data from fluorescence decay after photoconversion (FDAP) experiments. PyFDAP structures and analyses large FDAP datasets and features multiple fitting and plotting options.

Availability and implementation: PyFDAP was written in Python and runs on Ubuntu Linux, Mac OS X and Microsoft Windows operating systems. The software, a user guide and a test FDAP dataset are freely available for download from http://people.tuebingen.mpg.de/mueller-lab.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Algorithms*
Automation
Computer Graphics*
Fluorescence*
Photochemical Processes*
Software*