The Clustering of Regression Models Method with Applications in Gene Expression Data

DOI10.1111/j.1541-0420.2005.00498.xzbMath1097.62134OpenAlexW1985125533WikidataQ33254453 ScholiaQ33254453MaRDI QIDQ5492092

Steven G. Self, Li-Xuan Qin

Publication date: 12 October 2006

Published in: Biometrics (Search for Journal in Brave)

Full work available at URL: https://biostats.bepress.com/cgi/viewcontent.cgi?article=1072&context=uwbiostat

zbMATH Keywords

cluster analysismixture modelsgene clusteringgene expression analysis

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10)

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Uses Software

• fda (R)

Cites Work

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• Estimating the dimension of a model
• Functional data analysis
• The analysis of gene expression data. Methods and software
• Statistical modeling of large microarray data sets to identify stimulus-response profiles
• DNA Microarray Experiments: Biological and Technological Aspects
• Selecting Differentially Expressed Genes from Microarray Experiments
• Discrete Parameter Variation: Efficient Estimation of a Switching Regression Model
• Model-Based Gaussian and Non-Gaussian Clustering
• Empirical Bayes Analysis of a Microarray Experiment
• Model-Based Clustering, Discriminant Analysis, and Density Estimation
• Cluster analysis of gene expression dynamics

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