Workflows
What is a Workflow?Filters
An experiment which measured 15N labeled and unlabeled Chamydomonas reinhardtii samples at different ratios.
Associated Tutorial
This workflows is part of the tutorial M. tuberculosis Variant Analysis, available in the GTN
Features
- Includes Galaxy Workflow Tests
- Includes a Galaxy Workflow Report ...
Predict variants and drug resistance from M. tuberculosis sequence samples (Illumina)
Associated Tutorial
This workflows is part of the tutorial M. tuberculosis Variant Analysis, available in the GTN
Features
- Includes Galaxy Workflow Tests
...
Associated Tutorial
This workflows is part of the tutorial De Bruijn Graph Assembly, available in the GTN
Features
- Includes Galaxy Workflow Tests
- Includes a Galaxy Workflow Report ...
Associated Tutorial
This workflows is part of the tutorial De Bruijn Graph Assembly, available in the GTN
Features
- Includes Galaxy Workflow Tests
- Includes a Galaxy Workflow Report ...
Associated Tutorial
This workflows is part of the tutorial De Bruijn Graph Assembly, available in the GTN
Features
- Includes Galaxy Workflow Tests
- Includes a Galaxy Workflow Report ...
Barcode gene Extraction and Evaluation from Genome Skims (BeeGees) Snakemake workflow
Snakemake workflow for recovering high-quality barcode sequences at scale, built around MitoGeneExtractor and adapted for genome skims of museum specimens.
Contents
BioimageAIpub
A Python library to publish Bioimaging datasets to HuggingFace in AI-ready fashion.
Installation
git clone https://github.com/German-BioImaging/bioimageaipub/bioimageaipub.git
cd bioimageaipub
pip install -r requirements.txt
Usage
BioimageAIpub is supplied as a Python library. See demo/demo.ipynb for a Python notebook demonstrating the usage.
Citation
Acknowledgments
This project was supported by and is attributable to the German Cancer Research Center (DKFZ) ...
Type: Jupyter
Creators: Stefan Dvoretskii, Anwai Archit, Constantin Pape, Marco Nolden, Josh Moore, German Cancer Research Center (DKFZ), HMC Hub Health
Submitter: Stefan Dvoretskii
4D-BioReconX is a scalable and versatile framework designed to construct a comprehensive four-dimensional (4D) spatial transcriptomics atlas of whole animals at single-cell resolution. This approach enables us to track the intricate spatiotemporal dependencies of morphogenetic gradients and regenerative patterning. It runs based on spatial transcriptomics data, such as Stereo-seq (spatial enhanced resolution omics sequencing) data. Notably, we are still working on the improvement of performance ...