Using genetic markers to orient the edges in quantitative trait networks: The NEO software
- Standort
-
Deutsche Nationalbibliothek Frankfurt am Main
- ISSN
-
1752-0509
- Umfang
-
Online-Ressource
- Sprache
-
Englisch
- Anmerkungen
-
online resource.
- Erschienen in
-
Using genetic markers to orient the edges in quantitative trait networks: The NEO software ; volume:2 ; number:1 ; day:15 ; month:4 ; year:2008 ; pages:1-21 ; date:12.2008
BMC systems biology ; 2, Heft 1 (15.4.2008), 1-21, 12.2008
- Urheber
-
Aten, Jason E.
- Beteiligte Personen und Organisationen
-
Fuller, Tova F.
Lusis, Aldons J.
Horvath, Steve
SpringerLink (Online service)
- DOI
-
10.1186/1752-0509-2-34
- URN
-
urn:nbn:de:1111-2016072951966
- Rechteinformation
-
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
- Aten, Jason E.
- Fuller, Tova F.
- Lusis, Aldons J.
- Horvath, Steve
- SpringerLink (Online service)
Ähnliche Objekte (12)
DNA methylation age of human tissues and cell types
Gene network interconnectedness and the generalized topological overlap measure
Eigengene networks for studying the relationships between co-expression modules
Understanding network concepts in modules
WGCNA: an R package for weighted correlation network analysis
Network methods for describing sample relationships in genomic datasets: application to Huntington’s disease
Comparison of co-expression measures: mutual information, correlation, and model based indices
Random generalized linear model: a highly accurate and interpretable ensemble predictor
Multivariate variance-components analysis of longitudinal blood pressure measurements from the Framingham Heart Study
Significant variation in the performance of DNA methylation predictors across data preprocessing and normalization strategies
Epigenetic age provides insight into tissue origin in endometriosis
Cluster and propensity based approximation of a network
DNA methylation age of human tissues and cell types
Gene network interconnectedness and the generalized topological overlap measure
Eigengene networks for studying the relationships between co-expression modules
Understanding network concepts in modules
WGCNA: an R package for weighted correlation network analysis
Network methods for describing sample relationships in genomic datasets: application to Huntington’s disease
Comparison of co-expression measures: mutual information, correlation, and model based indices
Random generalized linear model: a highly accurate and interpretable ensemble predictor
Multivariate variance-components analysis of longitudinal blood pressure measurements from the Framingham Heart Study
Significant variation in the performance of DNA methylation predictors across data preprocessing and normalization strategies
Epigenetic age provides insight into tissue origin in endometriosis
Cluster and propensity based approximation of a network
DNA methylation age of human tissues and cell types
Gene network interconnectedness and the generalized topological overlap measure
Eigengene networks for studying the relationships between co-expression modules
Understanding network concepts in modules
WGCNA: an R package for weighted correlation network analysis
Network methods for describing sample relationships in genomic datasets: application to Huntington’s disease
Comparison of co-expression measures: mutual information, correlation, and model based indices
Random generalized linear model: a highly accurate and interpretable ensemble predictor
Multivariate variance-components analysis of longitudinal blood pressure measurements from the Framingham Heart Study
Significant variation in the performance of DNA methylation predictors across data preprocessing and normalization strategies
Epigenetic age provides insight into tissue origin in endometriosis