sc-SynO use case 1: cardiac glial cell identification in the validation datasets Version 2
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 sets, including the predicted clusters and those in close proximity.
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Created: 16th Oct 2020 at 11:26
Last updated: 21st Jan 2021 at 19:39
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Version 2 (latest) Created 20th Jan 2021 at 20:05 by Markus Wolfien
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Projects: iRhythmics
Institutions: University of Rostock
https://orcid.org/0000-0002-1887-4772
Projects that do not fall under current programmes.
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Web page: Not specified
The project addresses the generation and establishment of programmed pacemaker cells for an in vitro drug testing possibility to perform predictive tests. This may lead to an improved treatment of cardiac arrhythmias or an accurate identification of potential drug molecules at a very early stage of development. Important benefits will arise in verifying the safety of a wide variety of medicines while reducing animal testing. For more information you may visit our project website at ...
Programme: Independent Projects
Public web page: https://irhythmics.med.uni-rostock.de/
Application of the LoRAS oversampling approach on single-cell/single-nuclei data to annotate/identify specific cell populations in new data based on previously, manually curated data.
Submitter: Markus Wolfien
Biological problem addressed: Annotation
Investigation: 1 hidden item
Study: 1 hidden item
