Correction to: Combining heterogeneous subgroups with graph-structured variable selection priors for Cox regression
- Location
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Deutsche Nationalbibliothek Frankfurt am Main
- ISSN
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1471-2105
- Extent
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Online-Ressource
- Language
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Englisch
- Notes
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online resource.
- Bibliographic citation
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Correction to: Combining heterogeneous subgroups with graph-structured variable selection priors for Cox regression ; volume:23 ; number:1 ; day:11 ; month:1 ; year:2022 ; pages:1 ; date:12.2022
BMC bioinformatics ; 23, Heft 1 (11.1.2022), 1, 12.2022
- Creator
- Contributor
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SpringerLink (Online service)
- DOI
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10.1186/s12859-021-04552-3
- URN
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urn:nbn:de:101:1-2022042519235221735027
- Rights
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Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Last update
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15.08.2025, 7:37 AM CEST
Data provider
This object is provided by:
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Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Associated
- Madjar, Katrin
- Zucknick, Manuela
- Ickstadt, Katja
- Rahnenführer, Jörg
- SpringerLink (Online service)
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Weighted Cox regression for the prediction of heterogeneous patient subgroups
Hybrid clustering for microarray image analysis combining intensity and shape features
Improving adaptive seamless designs through Bayesian optimization
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Subgroup analyses and investigations of treatment effect heterogeneity in clinical dose-finding trials
Methods to characterize the behaviour of optimization algorithms
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Finite Bayesian mixture models with applications in spatial cluster analysis and bioinformatics
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Combining heterogeneous subgroups with graph-structured variable selection priors for Cox regression
Weighted Cox regression for the prediction of heterogeneous patient subgroups
Hybrid clustering for microarray image analysis combining intensity and shape features
Improving adaptive seamless designs through Bayesian optimization
Improving adaptive seamless designs through Bayesian optimization
Statistische Analyse von MCC-IMS-Messungen
Subgroup analyses and investigations of treatment effect heterogeneity in clinical dose-finding trials
Methods to characterize the behaviour of optimization algorithms
Statistische Methoden zur Identifikation von Patientensubgruppen aus Hochdurchsatzdaten
Finite Bayesian mixture models with applications in spatial cluster analysis and bioinformatics
Statistische Analyse und Modellierung von Clusterphänomenen bei Signalproteinen in der Plasmamembran