- Location
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Deutsche Nationalbibliothek Frankfurt am Main
- Extent
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1 Online-Ressource.
- Language
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Englisch
- Bibliographic citation
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Gene-expression memory-based prediction of cell lineages from scRNA-seq datasets ; volume:15 ; number:1 ; day:29 ; month:3 ; year:2024 ; pages:1-16 ; date:12.2024
Nature Communications ; 15, Heft 1 (29.3.2024), 1-16, 12.2024
- Creator
- Contributor
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SpringerLink (Online service)
- DOI
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10.1038/s41467-024-47158-y
- URN
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urn:nbn:de:101:1-2408131119554.247427912435
- Rights
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Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Last update
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14.08.2025, 9:19 PM CEST
Data provider
This object is provided by:
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Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Associated
- Eisele, A. S.
- Tarbier, M.
- Dormann, A. A.
- Pelechano, Vicent
- Suter, David
- SpringerLink (Online service)
Other Objects (12)
Author Correction: Gene-expression memory-based prediction of cell lineages from scRNA-seq datasets
Joint analysis of scATAC-seq datasets using epiConv
Using DenseFly algorithm for cell searching on massive scRNA-seq datasets
Choice of pre-processing pipeline influences clustering quality of scRNA-seq datasets
scReQTL: an approach to correlate SNVs to gene expression from individual scRNA-seq datasets
RNA-Seq analysis of blood meal induced gene-expression changes in Aedes aegypti ovaries
ScRNA-seq and ST-seq in liver research
scDART: integrating unmatched scRNA-seq and scATAC-seq data and learning cross-modality relationship simultaneously
Validating LIGER Integration Using scNMT-seq and SNARE-seq
RNA splicing analysis using heterogeneous and large RNA-seq datasets
An interpretable framework for clustering single-cell RNA-Seq datasets
GEMmaker: process massive RNA-seq datasets on heterogeneous computational infrastructure
Author Correction: Gene-expression memory-based prediction of cell lineages from scRNA-seq datasets
Joint analysis of scATAC-seq datasets using epiConv
Using DenseFly algorithm for cell searching on massive scRNA-seq datasets
Choice of pre-processing pipeline influences clustering quality of scRNA-seq datasets
scReQTL: an approach to correlate SNVs to gene expression from individual scRNA-seq datasets
RNA-Seq analysis of blood meal induced gene-expression changes in Aedes aegypti ovaries
ScRNA-seq and ST-seq in liver research
scDART: integrating unmatched scRNA-seq and scATAC-seq data and learning cross-modality relationship simultaneously
Validating LIGER Integration Using scNMT-seq and SNARE-seq
RNA splicing analysis using heterogeneous and large RNA-seq datasets
An interpretable framework for clustering single-cell RNA-Seq datasets
GEMmaker: process massive RNA-seq datasets on heterogeneous computational infrastructure
Author Correction: Gene-expression memory-based prediction of cell lineages from scRNA-seq datasets
Joint analysis of scATAC-seq datasets using epiConv
Using DenseFly algorithm for cell searching on massive scRNA-seq datasets
Choice of pre-processing pipeline influences clustering quality of scRNA-seq datasets
scReQTL: an approach to correlate SNVs to gene expression from individual scRNA-seq datasets
RNA-Seq analysis of blood meal induced gene-expression changes in Aedes aegypti ovaries
ScRNA-seq and ST-seq in liver research
scDART: integrating unmatched scRNA-seq and scATAC-seq data and learning cross-modality relationship simultaneously
Validating LIGER Integration Using scNMT-seq and SNARE-seq
RNA splicing analysis using heterogeneous and large RNA-seq datasets
An interpretable framework for clustering single-cell RNA-Seq datasets