DaKS - Datenrepository der Universität Kassel

DaKS ist das institutionelle Repositorium der Universität Kassel für Forschungsdaten. DaKS bietet die strukturierte Ablage von Forschungsdaten mit ihrer Beschreibung (Metadaten), die langfristige Archivierung von mindestens 10 Jahren und – falls gewünscht – die Veröffentlichung mit Angabe einer DOI.

DaKS wird von der Universitätsbibliothek und dem IT-Servicezentrum der Uni Kassel betreut und an der Philipps-Universität Marburg gehostet. Wir beraten Sie gern unter daks@uni-kassel.de.

Neuzugänge

Lineage Tracking and Asymmetric Inheritance Patterns of the Diatom Seminavis robusta [DiatomTrack source code]
(Universität Kassel, 2026-03-13) Ziebarth, Jonas
This repository belongs to the observation experiments for tracking lineages of Seminavis robusta. The connected work reconstructed the lineages and obtained individuals' timing of division and motility. Cells were entrained for 5 days prior under white light with 25 µmol phot / s in a 12:12 hour rhythm. The images were recorded with a modified Leica microscope (DMIL) and 770 nm light source and a band pass filter. Entrainment continued for the time of recording.
The software analyzes images to identify cells within each frame and extract their trajectories. It constructs cell lineages from these trajectories and allows for their subsequent editing. The processed results can be visualized and modified through a user interface. The workflow consists of three main steps: segmentation of raw images, cell tracking, and manual editing. Progress can be saved and reloaded at any stage. Upon completion of the final step, the software outputs at least a video file and a CSV file. The CSV file contains extracted data points organized by frame, along with unique identifiers that assign each point to a cell of a lineage tree.
The corresponding work defined the cell cycle as beginning at the first frame in which a cell was detected and concluding at the frame in which a child was identified.
A full documentation of the software is available under documentation.zip.
Use: Run main.py. For details see User_manual.
License: The tracking implementation adapts the SORT (Simple Online and Realtime Tracking) algorithm of Alex Bewley et al. Accordingly, this repository is distributed under the GPL-3.0 License. See LICENSE for details.
Lineage Tracking and Asymmetric Inheritance Patterns of the Diatom Seminavis robusta [U-Net Training source code]
(Universität Kassel, 2026-03-13) Ziebarth, Jonas
This repository belongs to the observation experiments for tracking lineages of Seminavis robusta. The connected work reconstructed the lineages and obtained individuals' timing of division and motility. Cells were entrained for 5 days prior under white light with 25 µmol phot / s in a 12:12 hour rhythm. The images were recorded with a modified Leica microscope (DMIL) and 770 nm light source and a band pass filter. Entrainment continued for the time of recording.
This repository contains code for training a U-Net model to segment microscopy images into three classes: cell aggregates, single cells, and background. The implementation is adapted from Lee et al. (DOI: 10.1038/s41598-022-12532-7), originally published under the MIT License. During training, the code computes standard and custom segmentation metrics at user-defined intervals (in a separate process to avoid I/O bottlenecks). After the final epoch, these metrics are automatically plotted and saved to the output directory. The provided version includes image resizing functionality and uses segmentation masks generated by tools developed for this work. Furthermore, code for testing on unseen data, all (pickled) metrics and training results, and image data are provided.
Use: Configure paths (training data/output directory), learning rate, epochs, and metric calculation frequency in config.py. Set the random seed and CUDA devices in main.py. Run main.py from IDE.
License: This repository is licensed under the European Union Public Licence v. 1.2 (EUPL-1.2). Portions of the code originating from Lee et al. are licensed under the MIT License.
In accordance with the respective licensing requirements, both license texts are included in this repository. See the LICENCE (EUPL-1.2) and LICENCE_MIT files for details.
Lineage Tracking and Asymmetric Inheritance Patterns of the Diatom Seminavis robusta [Training image mask generation source code]
(Universität Kassel, 2026-03-13) Ziebarth, Jonas
This repository belongs to the observation experiments for tracking lineages of Seminavis robusta. The connected work reconstructed the lineages and obtained individuals' timing of division and motility. Cells were entrained for 5 days prior under white light with 25 µmol phot / s in a 12:12 hour rhythm. The images were recorded with a modified Leica microscope (DMIL) and 770 nm light source and a band pass filter. Entrainment continued for the time of recording.
The provided code automates the creation of training and test datasets for the training of U-Net. It generates the required directory structure at the location of the raw data and produces binary masks as PNG. The masks encode a coarse and fine label for the two object classes (cell aggregates and single cell).
Use: Specify the path to the raw data in main.py. Optionally, adjust the parameters of TrainingImageGenerator to suit your data; the default settings already yield satisfactory results for the example dataset. Run main.py.
License: This code is licensed under the European Union Public Licence v. 1.2. See the LICENSE file for details.
Lineage Tracking and Asymmetric Inheritance Patterns of the Diatom Seminavis robusta [Raspberry Pi LED-Matrix source code]
(Universität Kassel, 2026-02-11) Ziebarth, Jonas
This repository belongs to the observation experiments for tracking lineages of Seminavis robusta. The connected work reconstructed the lineages and obtained individuals' timing of division and motility. Cells were entrained for 5 days prior under white light with 25 µmol phot / s in a 12:12 hour rhythm. The images were recorded with a modified Leica microscope (DMIL) and 770 nm light source and a band pass filter. Entrainment continued for the time of recording.
This Python script uses an ssh tunnel to connect two Raspberry Pi (3B, Zero) computers via USB if the USB is configured for an Ethernet connection. A number of LED panels can be connected to the GPIO pins of the remote Raspberry Pi (using a HAT) and setup for entrainment of a diatom culture with flexible rhythms while using the local Raspberry Pi for observations with sensors. This combines the functionalities of the LED-matrix library by Henner Zeller and sensorpi by Nikolai Weidt.
The repository contains a full copy of the version of LED-matrix library including the file manual_color_fill.py as by provisions of the original author. The file is also separately available in the root location. The setup file contains the script for initiating the connection and starting sensorpi.

Use: Connect two Raspberry Pi and configure Ethernet via USB as well as ssh settings. Install LED-matrix library on the remote machine and sensorpi on the local machine. Run setup.py on the local machine from shell. Add -h or --help for info about options.

License: This code and the included third party libraries are licensed under the GNU General Public License Version 3.0. See the LICENSE file for details.
Lineage Tracking and Asymmetric Inheritance Patterns of the Diatom Seminavis robusta [Raw data]
(Universität Kassel, 2026-02-21) Ziebarth, Jonas
This repository belongs to the observation experiments for tracking lineages of Seminavis robusta. The connected work reconstructed the lineages and obtained individuals' timing of division and motility. Cells were entrained for 5 days prior under white light with 25 µmol phot / s in a 12:12 hour rhythm. The images were recorded with a modified Leica microscope (DMIL) and 770 nm light source and a band pass filter. Entrainment continued for the time of recording.
These directories contain the full-scale raw data from the experiments. Images were captured at 10-second intervals using IC Capture (The Imaging Source).
Directory names include the starting date, experiment type, exposure time, gain (two decimal places), gamma (two decimal places), and sharpness parameter.
Image filenames end with a timestamp. Preceding the timestamp (in order) are: the researcher’s name (Jonas Ziebarth), magnification (4x), lighting (IR-LED), observed species (Seminavis robusta), and experiment type. In the raw images, 129 pixels equate to 100 µm.
Use: The data is processed by the Diatom Tracker program (part of the connected work). In the first file selection dialogue, select the directories for raw data and saving. The program subsequently reads the files, reduces image resolution, segments content, and finally exports results to video and CSV files.

This repository item contains a dummy file only. The actual dataset is too large to be downloaded directly via the repository and is therefore stored in a separate location. It is approx. 8 TB in size.
To obtain the full dataset, please use the repository’s request function (click on the lock symbol next to the file). After submitting a request, data transfer will be arranged individually with the requester (e.g. via secure download, physical media, or institutional transfer), depending on size and access requirements.

The recording of data started after the beginning of the dark phase. The offsets for the respective data sets are:
20240121_... +13 frames / 130 s
20240217_... +384 frames / 3840 s
20240301_... +21 frames / 210 s