Unsupervised spatially embedded deep representation of spatial transcriptomics
- Standort
-
Deutsche Nationalbibliothek Frankfurt am Main
- Umfang
-
1 Online-Ressource.
- Sprache
-
Englisch
- Erschienen in
-
Unsupervised spatially embedded deep representation of spatial transcriptomics ; volume:16 ; number:1 ; day:12 ; month:1 ; year:2024 ; pages:1-15 ; date:12.2024
Genome medicine ; 16, Heft 1 (12.1.2024), 1-15, 12.2024
- Urheber
-
Xu, Hang
Fu, Huazhu
Long, Yahui
Ang, Kok Siong
Sethi, Raman
Chong, Kelvin
Li, Mengwei
Uddamvathanak, Rom
Lee, Hong Kai
Ling, Jingjing
Chen, Ao
Shao, Ling
Liu, Longqi
Chen, Jinmiao
- Beteiligte Personen und Organisationen
-
SpringerLink (Online service)
- DOI
-
10.1186/s13073-024-01283-x
- URN
-
urn:nbn:de:101:1-2024032515161016203030
- Rechteinformation
-
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
-
14.08.2025, 10:50 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
- Xu, Hang
- Fu, Huazhu
- Long, Yahui
- Ang, Kok Siong
- Sethi, Raman
- Chong, Kelvin
- Li, Mengwei
- Uddamvathanak, Rom
- Lee, Hong Kai
- Ling, Jingjing
- Chen, Ao
- Shao, Ling
- Liu, Longqi
- Chen, Jinmiao
- SpringerLink (Online service)
Ähnliche Objekte (12)
A nature inspired modularity function for unsupervised learning involving spatially embedded networks
Spatially resolved transcriptomics in immersive environments
Spatially resolved transcriptomics in immersive environments
Kalman contrastive unsupervised representation learning
Spatially Resolved Transcriptomics Technology Facilitates Cancer Research
Spatially aware dimension reduction for spatial transcriptomics
Deciphering spatial domains from spatially resolved transcriptomics through spatially regularized deep graph networks
Unsupervised representation learning with Minimax distance measures
Spatially resolved transcriptomics reveals plant host responses to pathogens
SRTsim: spatial pattern preserving simulations for spatially resolved transcriptomics
Bild-Raum-Wissenschaft : studies on spatially embedded art
CoSTA: unsupervised convolutional neural network learning for spatial transcriptomics analysis
A nature inspired modularity function for unsupervised learning involving spatially embedded networks
Spatially resolved transcriptomics in immersive environments
Spatially resolved transcriptomics in immersive environments
Kalman contrastive unsupervised representation learning
Spatially Resolved Transcriptomics Technology Facilitates Cancer Research
Spatially aware dimension reduction for spatial transcriptomics
Deciphering spatial domains from spatially resolved transcriptomics through spatially regularized deep graph networks
Unsupervised representation learning with Minimax distance measures
Spatially resolved transcriptomics reveals plant host responses to pathogens
SRTsim: spatial pattern preserving simulations for spatially resolved transcriptomics
Bild-Raum-Wissenschaft : studies on spatially embedded art
CoSTA: unsupervised convolutional neural network learning for spatial transcriptomics analysis
A nature inspired modularity function for unsupervised learning involving spatially embedded networks
Spatially resolved transcriptomics in immersive environments
Spatially resolved transcriptomics in immersive environments
Kalman contrastive unsupervised representation learning
Spatially Resolved Transcriptomics Technology Facilitates Cancer Research
Spatially aware dimension reduction for spatial transcriptomics
Deciphering spatial domains from spatially resolved transcriptomics through spatially regularized deep graph networks
Unsupervised representation learning with Minimax distance measures
Spatially resolved transcriptomics reveals plant host responses to pathogens
SRTsim: spatial pattern preserving simulations for spatially resolved transcriptomics
Bild-Raum-Wissenschaft : studies on spatially embedded art