A nested unsupervised approach to identifying novel molecular subtypes

DOI10.3150/bj/1106314845zbMath1055.62120OpenAlexW2133587468MaRDI QIDQ1763095

Giovanni Parmigiani, Elizabeth S. Garrett

Publication date: 21 February 2005

Published in: Bernoulli (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.3150/bj/1106314845

zbMATH Keywords

Bayesian modelgene expressionlung cancerclass discovery

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Applications of statistics to biology and medical sciences; meta analysis (62P10) Medical applications (general) (92C50) Biochemistry, molecular biology (92C40)

Related Items (1)

Modeling dependent gene expression

Cites Work

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• Design and analysis of DNA microarray investigations.
• How Many Clusters? Which Clustering Method? Answers Via Model-Based Cluster Analysis
• Importance of replication in microarray gene expression studies: Statistical methods and evidence from repetitive cDNA hybridizations
• A Statistical Framework for Expression-Based Molecular Classification in Cancer

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