Inferring gene regulatory networks from single-cell multiome data using atlas-scale external data
- Standort
-
Deutsche Nationalbibliothek Frankfurt am Main
- Umfang
-
1 Online-Ressource.
- Sprache
-
Englisch
- Erschienen in
-
Inferring gene regulatory networks from single-cell multiome data using atlas-scale external data ; day:12 ; month:4 ; year:2024 ; pages:1-11
Nature biotechnology ; (12.4.2024), 1-11
- Urheber
-
Yuan, Qiuyue
Duren, Zhana
- Beteiligte Personen und Organisationen
-
SpringerLink (Online service)
- DOI
-
10.1038/s41587-024-02182-7
- URN
-
urn:nbn:de:101:1-2406240935434.747956790092
- Rechteinformation
-
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
-
14.08.2025, 10:53 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
- Yuan, Qiuyue
- Duren, Zhana
- SpringerLink (Online service)
Ähnliche Objekte (12)
Inferring gene regulatory networks from single-cell data: a mechanistic approach
OncoNEM: inferring tumor evolution from single-cell sequencing data
Inferring gene regulatory networks from asynchronous microarray data with AIRnet
Inferring gene regulatory networks from classified microarray data: Initial results
Inferring replication timing and proliferation dynamics from single-cell DNA sequencing data
Inferring microRNA and transcription factor regulatory networks in heterogeneous data
Inferring interaction type in gene regulatory networks using co-expression data
New avenues for systematically inferring cell-cell communication: through single-cell transcriptomics data
Inferring the kinetics of stochastic gene expression from single-cell RNA-sequencing data
Reference-free inferring of transcriptomic events in cancer cells on single-cell data
Inferring extrinsic noise from single-cell gene expression data using approximate Bayesian computation
Inferring gene regulatory networks and cellular phases from time-resolved transcriptomics data
Inferring gene regulatory networks from single-cell data: a mechanistic approach
OncoNEM: inferring tumor evolution from single-cell sequencing data
Inferring gene regulatory networks from asynchronous microarray data with AIRnet
Inferring gene regulatory networks from classified microarray data: Initial results
Inferring replication timing and proliferation dynamics from single-cell DNA sequencing data
Inferring microRNA and transcription factor regulatory networks in heterogeneous data
Inferring interaction type in gene regulatory networks using co-expression data
New avenues for systematically inferring cell-cell communication: through single-cell transcriptomics data
Inferring the kinetics of stochastic gene expression from single-cell RNA-sequencing data
Reference-free inferring of transcriptomic events in cancer cells on single-cell data
Inferring extrinsic noise from single-cell gene expression data using approximate Bayesian computation
Inferring gene regulatory networks and cellular phases from time-resolved transcriptomics data
Inferring gene regulatory networks from single-cell data: a mechanistic approach
OncoNEM: inferring tumor evolution from single-cell sequencing data
Inferring gene regulatory networks from asynchronous microarray data with AIRnet
Inferring gene regulatory networks from classified microarray data: Initial results
Inferring replication timing and proliferation dynamics from single-cell DNA sequencing data
Inferring microRNA and transcription factor regulatory networks in heterogeneous data
Inferring interaction type in gene regulatory networks using co-expression data
New avenues for systematically inferring cell-cell communication: through single-cell transcriptomics data
Inferring the kinetics of stochastic gene expression from single-cell RNA-sequencing data
Reference-free inferring of transcriptomic events in cancer cells on single-cell data
Inferring extrinsic noise from single-cell gene expression data using approximate Bayesian computation