On biological validity indices for soft clustering algorithms for gene expression data

DOI10.1016/j.csda.2010.12.003zbMath1328.62392OpenAlexW2005226337MaRDI QIDQ901585

Han-Ming Wu

Publication date: 12 January 2016

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.csda.2010.12.003

zbMATH Keywords

fuzzy clusteringgene expressionsoft clusteringmicroarray data analysisfuzzy c-meansbiological validity indicesfuzzy cluster validity

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Applications of statistics to biology and medical sciences; meta analysis (62P10) Multivariate analysis and fuzziness (62H86)

Related Items (4)

Multiple suboptimal solutions for prediction rules in gene expression data ⋮ Multiple hypothesis testing and clustering with mixtures of non-central \(t\)-distributions applied in microarray data analysis ⋮ Spontaneous Clustering via Minimum Gamma-Divergence ⋮ Comparison of clustering algorithms on generalized propensity score in observational studies: a simulation study

Uses Software

• R
• Silhouettes
• e1071
• clValid
• clue
• clusfind
• clustervalidation

Cites Work

• Unnamed Item
• Separation index and partial membership for clustering
• Cluster-wise assessment of cluster stability
• Silhouettes: a graphical aid to the interpretation and validation of cluster analysis
• Consensus clustering: A resampling-based method for class discovery and visualization of gene expression microarray data
• FUZZY SHELL-CLUSTERING AND APPLICATIONS TO CIRCLE DETECTION IN DIGITAL IMAGES
• Finding Groups in Data
• Model-Based Clustering, Discriminant Analysis, and Density Estimation
• A Fuzzy Relative of the ISODATA Process and Its Use in Detecting Compact Well-Separated Clusters

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