Tools to process images and FCS data for FCS-calibrated imaging and high-throughput FCS. The package contains tools to batch fit auto-correlation curves to mathematical models, compute an FCS-calibration curve, and apply the FCS-calibration to images. Refer to the Wiki for more information. For the most recent binary installers to FCSFitM (setup_FCSFitM) and FCSCalibration (setup_FCSCalibration) download the files from the binaries link. The source code can be found following the source code link.
The Fluctuation Analyzer is a software tool for the interactive as well as automated processing of fluorescence auto- and cross-correlation spectroscopy (FCS/FCCS) data. It can read raw data, i.e., one-or two-channel photon streams, from various commercial suppliers of FCS/FCCS data acquisition equipment, organize such data in processing sessions by file-based management, calculate temporal auto- and cross-correlation functions, correct for photobleaching, cross-talk, and background signal and fit the data with appropriate model functions before saving the results. Version 15.02.23 can be downloaded from here. For more recent versions follow the Website link.
The CellCognition framework is designed to combine object detection and supervised machine learning for classification of morphologies with time-resolved analysis by single-cell tracking. This enables measurements of progression through morphology stages and kinetic readouts at the single-cell level.
The software was designed to run on the three major platforms (Windows, Mac OSX, Linux) at high speed with high convenience. We therefore combined C++ image processing based on VIGRA with a Python-based workflow engine and a Qt-based graphical user-interface.
Microscopy Pipeline Constructor (MyPiC) allows intuitive set-up of complex time-lapse experiments for Zeiss confocal microscopes (ZEN black). Different modules can be combined to an experiment-tailored workflow: Hardware-(reflection), object-based autofocus (cell tracking), grid scanning, tile images, and adaptive feedback microscopy for rare event detection, automated FRAP and FCS. MyPiC replaces the AutofocusScreen (AFS3.1.3) macro. Previous versions of AFS can be downloaded from EMBLEM website. AFS compatible with LSM software can be found at the Zeiss website Zeiss website. Follow the Wiki instructions to install the software. A packaged version can be found here.
FCSRunner is a VBA macro for Zeiss confocals (ZEN black) to acquire multi-position FCS measurements. FCSRunner acquires a reference image, fluorescence (cross)correlation spectroscopy (F(C)CS) measurements, and save FCS positions to a xml file. Points need to be specified manually. The tool can be used to create data for FCS-calibrated imaging. Refer to the Wiki on how to install and use this tool. A packaged version can be found here.
ImageJ/FiJi tools to be used with the Zeiss VBA macro Microscopy Pipeline Constructor to perform adaptive feedback microscopy experiments. The user can specify segmentation parameters and commands to be sent to the microscope for initiating a different imaging, FRAP or FC(C)S pipeline. A packaged version can be found here.
Quantitative microscopy relies on imaging of large cell numbers but is often hampered by time-consuming manual selection of specific cells. The 'Micropilot' software automatically detects cells of interest and launches complex imaging experiments including three-dimensional multicolor time-lapse or fluorescence recovery after photobleaching in live cells. In three independent experimental setups this allowed us to statistically analyze biological processes in detail and is thus a powerful tool for systems biology.
Provides complete kinetochore tracking datasets during the first meiotic division in mouse oocytes. All kinetochores from five oocytes were tracked from nuclear envelope breakdown (NEBD) to anaphase onset of meiosis I. The source images and the 4D datasets can be browsed interactively using the Java applet Kinetochore Track Viewer, plots from the analysis, and download the images and the datasets, providing examples for mining the datasets.