Pan-cancer identification of clinically relevant genomic subtypes using outcome-weighted integrative clustering
- Location
-
Deutsche Nationalbibliothek Frankfurt am Main
- ISSN
-
1756-994X
- Extent
-
Online-Ressource
- Language
-
Englisch
- Notes
-
online resource.
- Bibliographic citation
-
Pan-cancer identification of clinically relevant genomic subtypes using outcome-weighted integrative clustering ; volume:12 ; number:1 ; day:3 ; month:12 ; year:2020 ; pages:1-13 ; date:12.2020
Genome medicine ; 12, Heft 1 (3.12.2020), 1-13, 12.2020
- Creator
-
Arora, Arshi
Olshen, Adam B.
Seshan, Venkatraman E.
Shen, Ronglai
- Contributor
-
SpringerLink (Online service)
- DOI
-
10.1186/s13073-020-00804-8
- URN
-
urn:nbn:de:101:1-2021011219562595843224
- Rights
-
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Last update
-
15.08.2025, 7:33 AM CEST
Data provider
This object is provided by:
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Associated
- Arora, Arshi
- Olshen, Adam B.
- Seshan, Venkatraman E.
- Shen, Ronglai
- SpringerLink (Online service)
Other Objects (12)
Pan-cancer patterns of cuproptosis markers reveal biologically and clinically relevant cancer subtypes
Clinically conserved genomic subtypes of gastric adenocarcinoma
Pan-cancer analysis identifies telomerase-associated signatures and cancer subtypes
Auto-weighted multiple kernel tensor clustering
The LINEX Weighted k-Means Clustering
Identification of Asthma Subtypes Using Clustering Methodologies
Multi-modal molecular determinants of clinically relevant osteoporosis subtypes
FGFR1 expression defines clinically distinct subtypes in pancreatic cancer
GScluster: network-weighted gene-set clustering analysis
Structure-function clustering in weighted brain networks
A graph clustering algorithm based on a clustering coefficient for weighted graphs
Lag penalized weighted correlation for time series clustering
Pan-cancer patterns of cuproptosis markers reveal biologically and clinically relevant cancer subtypes
Clinically conserved genomic subtypes of gastric adenocarcinoma
Pan-cancer analysis identifies telomerase-associated signatures and cancer subtypes
Auto-weighted multiple kernel tensor clustering
The LINEX Weighted k-Means Clustering
Identification of Asthma Subtypes Using Clustering Methodologies
Multi-modal molecular determinants of clinically relevant osteoporosis subtypes
FGFR1 expression defines clinically distinct subtypes in pancreatic cancer
GScluster: network-weighted gene-set clustering analysis
Structure-function clustering in weighted brain networks
A graph clustering algorithm based on a clustering coefficient for weighted graphs
Lag penalized weighted correlation for time series clustering
Pan-cancer patterns of cuproptosis markers reveal biologically and clinically relevant cancer subtypes
Clinically conserved genomic subtypes of gastric adenocarcinoma
Pan-cancer analysis identifies telomerase-associated signatures and cancer subtypes
Auto-weighted multiple kernel tensor clustering
The LINEX Weighted k-Means Clustering
Identification of Asthma Subtypes Using Clustering Methodologies
Multi-modal molecular determinants of clinically relevant osteoporosis subtypes
FGFR1 expression defines clinically distinct subtypes in pancreatic cancer
GScluster: network-weighted gene-set clustering analysis
Structure-function clustering in weighted brain networks
A graph clustering algorithm based on a clustering coefficient for weighted graphs