LSH-GAN enables in-silico generation of cells for small sample high dimensional scRNA-seq data
- Location
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Deutsche Nationalbibliothek Frankfurt am Main
- ISSN
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2399-3642
- Extent
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Online-Ressource
- Language
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Englisch
- Notes
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online resource.
- Bibliographic citation
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LSH-GAN enables in-silico generation of cells for small sample high dimensional scRNA-seq data ; volume:5 ; number:1 ; day:10 ; month:6 ; year:2022 ; pages:1-9 ; date:12.2022
Communications biology ; 5, Heft 1 (10.6.2022), 1-9, 12.2022
- Creator
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Lall, Snehalika
Ray, Sumanta
Bandyopadhyay, Sanghamitra
- Contributor
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SpringerLink (Online service)
- DOI
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10.1038/s42003-022-03473-y
- URN
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urn:nbn:de:101:1-2022080400460219944220
- Rights
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Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Last update
-
15.08.2025, 7:25 AM CEST
Data provider
This object is provided by:
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Associated
- Lall, Snehalika
- Ray, Sumanta
- Bandyopadhyay, Sanghamitra
- SpringerLink (Online service)
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