- Standort
-
Deutsche Nationalbibliothek Frankfurt am Main
- ISSN
-
1862-5355
- Umfang
-
Online-Ressource
- Sprache
-
Englisch
- Anmerkungen
-
online resource.
- Erschienen in
-
Adapted single-cell consensus clustering (adaSC3) ; volume:14 ; number:4 ; day:15 ; month:12 ; year:2020 ; pages:885-896 ; date:12.2020
Advances in data analysis and classification ; 14, Heft 4 (15.12.2020), 885-896, 12.2020
- Urheber
- Beteiligte Personen und Organisationen
-
SpringerLink (Online service)
- DOI
-
10.1007/s11634-020-00428-1
- URN
-
urn:nbn:de:101:1-2021030923420242692797
- Rechteinformation
-
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
-
15.08.2025, 07:28 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
- Fuetterer, Cornelia
- Augustin, Thomas
- Fuchs, Christiane
- SpringerLink (Online service)
Ähnliche Objekte (12)
Building consensus for Ada 9X
Multiresolution Consensus Clustering in Networks
Identification of cancer subtypes from single-cell RNA-seq data using a consensus clustering method
Consensus clustering for Bayesian mixture models
Implicit consensus clustering from multiple graphs
scConsensus: combining supervised and unsupervised clustering for cell type identification in single-cell RNA sequencing data
Representation learning for clustering via building consensus
JOINTLY: interpretable joint clustering of single-cell transcriptomes
scSTEM: clustering pseudotime ordered single-cell data
Bayesian Inference for Single-cell Clustering and Imputing
Consensus clustering applied to multi-omics disease subtyping
Orthogonal multimodality integration and clustering in single-cell data
Building consensus for Ada 9X
Multiresolution Consensus Clustering in Networks
Identification of cancer subtypes from single-cell RNA-seq data using a consensus clustering method
Consensus clustering for Bayesian mixture models
Implicit consensus clustering from multiple graphs
scConsensus: combining supervised and unsupervised clustering for cell type identification in single-cell RNA sequencing data
Representation learning for clustering via building consensus
JOINTLY: interpretable joint clustering of single-cell transcriptomes
scSTEM: clustering pseudotime ordered single-cell data
Bayesian Inference for Single-cell Clustering and Imputing
Consensus clustering applied to multi-omics disease subtyping
Orthogonal multimodality integration and clustering in single-cell data
Building consensus for Ada 9X
Multiresolution Consensus Clustering in Networks
Identification of cancer subtypes from single-cell RNA-seq data using a consensus clustering method
Consensus clustering for Bayesian mixture models
Implicit consensus clustering from multiple graphs
scConsensus: combining supervised and unsupervised clustering for cell type identification in single-cell RNA sequencing data
Representation learning for clustering via building consensus
JOINTLY: interpretable joint clustering of single-cell transcriptomes
scSTEM: clustering pseudotime ordered single-cell data
Bayesian Inference for Single-cell Clustering and Imputing
Consensus clustering applied to multi-omics disease subtyping