Hydro-Seq enables contamination-free high-throughput single-cell RNA-sequencing for circulating tumor cells
- Standort
-
Deutsche Nationalbibliothek Frankfurt am Main
- ISSN
-
2041-1723
- Umfang
-
Online-Ressource
- Sprache
-
Englisch
- Anmerkungen
-
online resource.
- Erschienen in
-
Hydro-Seq enables contamination-free high-throughput single-cell RNA-sequencing for circulating tumor cells ; volume:10 ; number:1 ; day:15 ; month:5 ; year:2019 ; pages:1-11 ; date:12.2019
Nature Communications ; 10, Heft 1 (15.5.2019), 1-11, 12.2019
- Urheber
-
Cheng, Yu-Heng
Chen, Yu-Chih
Lin, Eric
Brien, Riley
Jung, Seungwon
Chen, Yu-Ting
Lee, Woncheol
Hao, Zhijian
Sahoo, Saswat
Min Kang, Hyun
Cong, Jason
Burness, Monika
Nagrath, Sunitha
S. Wicha, Max
Yoon, Euisik
- Beteiligte Personen und Organisationen
-
SpringerLink (Online service)
- DOI
-
10.1038/s41467-019-10122-2
- URN
-
urn:nbn:de:101:1-2019090121145851314675
- Rechteinformation
-
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
- 15.08.2025, 07:24 MESZ
Datenpartner
Dieses Objekt wird bereitgestellt von:
Deutsche Nationalbibliothek. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Deutsche Nationalbibliothek. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Beteiligte
- Cheng, Yu-Heng
- Chen, Yu-Chih
- Lin, Eric
- Brien, Riley
- Jung, Seungwon
- Chen, Yu-Ting
- Lee, Woncheol
- Hao, Zhijian
- Sahoo, Saswat
- Min Kang, Hyun
- Cong, Jason
- Burness, Monika
- Nagrath, Sunitha
- S. Wicha, Max
- Yoon, Euisik
- SpringerLink (Online service)
Ähnliche Objekte (12)
Virus expression detection reveals RNA-sequencing contamination in TCGA
Single-cell RNA-sequencing of the brain
Characterization of iCell cardiomyocytes using single-cell RNA-sequencing methods
Statistical power analysis for single-cell RNA-sequencing
Sctensor detects many-to-many cell–cell interactions from single cell RNA-sequencing data
Cell-type-specific co-expression inference from single cell RNA-sequencing data
Dual indexed library design enables compatibility of in-Drop single-cell RNA-sequencing with exAMP chemistry sequencing platforms
Autophagy-prominent cell clusters among human lens epithelial cells: integrated single-cell RNA-sequencing analysis
Single-cell RNA-sequencing of stria vascularis cells in the adult Slc26a4 -/- mouse
Deep generative models for designing single-cell RNA-sequencing experiments
A systematic evaluation of single-cell RNA-sequencing imputation methods
RESCUE: imputing dropout events in single-cell RNA-sequencing data
Virus expression detection reveals RNA-sequencing contamination in TCGA
Single-cell RNA-sequencing of the brain
Characterization of iCell cardiomyocytes using single-cell RNA-sequencing methods
Statistical power analysis for single-cell RNA-sequencing
Sctensor detects many-to-many cell–cell interactions from single cell RNA-sequencing data
Cell-type-specific co-expression inference from single cell RNA-sequencing data
Dual indexed library design enables compatibility of in-Drop single-cell RNA-sequencing with exAMP chemistry sequencing platforms
Autophagy-prominent cell clusters among human lens epithelial cells: integrated single-cell RNA-sequencing analysis
Single-cell RNA-sequencing of stria vascularis cells in the adult Slc26a4 -/- mouse
Deep generative models for designing single-cell RNA-sequencing experiments
A systematic evaluation of single-cell RNA-sequencing imputation methods
RESCUE: imputing dropout events in single-cell RNA-sequencing data
Virus expression detection reveals RNA-sequencing contamination in TCGA
Single-cell RNA-sequencing of the brain
Characterization of iCell cardiomyocytes using single-cell RNA-sequencing methods
Statistical power analysis for single-cell RNA-sequencing
Sctensor detects many-to-many cell–cell interactions from single cell RNA-sequencing data
Cell-type-specific co-expression inference from single cell RNA-sequencing data
Dual indexed library design enables compatibility of in-Drop single-cell RNA-sequencing with exAMP chemistry sequencing platforms
Autophagy-prominent cell clusters among human lens epithelial cells: integrated single-cell RNA-sequencing analysis
Single-cell RNA-sequencing of stria vascularis cells in the adult Slc26a4 -/- mouse
Deep generative models for designing single-cell RNA-sequencing experiments
A systematic evaluation of single-cell RNA-sequencing imputation methods