Data files
NMN formation by NamPT was measured using LC-MS as described in supplementary information
Creators: Ines Heiland, Dorothee Houry
Submitter: Ines Heiland
Data used for training or testing of the model
Creator: Hannah Kinmonth-Schultz
Submitter: Hannah Kinmonth-Schultz
Visualization of the workflow demonstrating a step-by-step explanation for a sc-SynO analysis. a) Several or one snRNA-Seq or scRNA-Seq fastq datasets can be used as an input. Here, we identify our cell population of interest and provide raw or normalized read counts of this specific population to sc-SynO for training. b) Further information for cluster annotation and processed count data are serving as input for the core algorithm. c) Based on the data input, we utilize the LoRAS synthetic
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Creators: Markus Wolfien, Saptarshi Bej
Submitter: Markus Wolfien
Validation of the sc-SynO model for the first use case of cardiac glial cell annotation. UMAP representation of the manually clustered Bl6 dataset of Wolfien et al. (2020) Precicted cells of sc-SynO are highlighted in blue, cells not chosen are grey. UMAP representation of the manually clustered dataset of Vidal (2019). Precicted cells of sc-SynO are highlighted in blue, cells not chosen are grey. Average expression of the respective top five cardiac glial cell marker genes for both validation
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Creators: Markus Wolfien, Saptarshi Bej
Submitter: Markus Wolfien
Validation of the sc-SynO model for the second use case of proliferative cardiomyocytes annotation. a) UMAP representation of the manually clustered single-nuclei dataset of Linscheid et al. (2019) Precicted cells of sc-SynO are highlighted in blue (based on top 20 selected features in the training model), red (based on top 100 selected features in the training model) cells not chosen are grey. b) UMAP representation of the manually clustered dataset of Vidal et al. (2020). PPrecicted cells of
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Creators: Markus Wolfien, Saptarshi Bej
Submitter: Markus Wolfien
The NFDI4Health Task Force COVID-19 Metadata Schema Mapping (Metadata Schema Mapping) contains a list of properties describing a resource being registered in the Study Hub of the NFDI4Health Task Force COVID-19 (Study Hub) and how those properties align with other standards (FHIRE, CDISK, DRKS, ITRCP)
Creators: None
Submitter: Martin Golebiewski
The NFDI4Health Task Force COVID-19 Metadata Schema (Metadata Schema) contains a list of properties describing a resource being registered in the Study Hub of the NFDI4Health Task Force COVID-19 (Study Hub).
Creators: Aliaksandra Shutsko, Carsten Oliver Schmidt, Johannes Darms, Martin Golebiewski, Moritz Lehne, Matthias Löbe, Sophie Klopfenstein, Carina Nina Vorisek
Submitter: Martin Golebiewski
More information can be found on GitHub: https://github.com/zhxiaokang/fishDefensome/tree/main/developmentalStages/zebrafish
Creator: Xiaokang Zhang
Submitter: Xiaokang Zhang
Source code and relevant files can be found on GitHub: https://github.com/zhxiaokang/fishDefensome/tree/main/developmentalStages/stickleback
Creator: Xiaokang Zhang
Submitter: Xiaokang Zhang
Creators: Xiaokang Zhang, Marta Eide, Odd André Karlsen, Inge Jonassen, Anders Goksøyr, Jared V. Goldstone; John Stegeman
Submitter: Xiaokang Zhang