Clustering of unevenly sampled gene expression time-series data

DOI10.1016/j.fss.2004.10.014zbMath1066.92025DBLPjournals/fss/Moller-LevetKCYW05OpenAlexW2096295012WikidataQ57261298 ScholiaQ57261298MaRDI QIDQ1776502

Niranjan Chakravarthy

Publication date: 12 May 2005

Published in: Fuzzy Sets and Systems (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.fss.2004.10.014

zbMATH Keywords

Fuzzy clusteringGene expressionUnevenly sampled short time series

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Applications of statistics to biology and medical sciences; meta analysis (62P10) Biochemistry, molecular biology (92C40) Genetics and epigenetics (92D10) Computational methods for problems pertaining to biology (92-08)

Related Items (6)

An evaluation of a novel approach for clustering genes with dissimilar replicates ⋮ Clustering of short time-course gene expression data with dissimilar replicates ⋮ Unsupervised minor prototype detection using an adaptive population partitioning algorithm ⋮ Clustering of temporal gene expression data by regularized spline regression and an energy based similarity measure ⋮ A novel HMM-based clustering algorithm for the analysis of gene expression time-course data ⋮ Testing the significance of cell-cycle patterns in time-course microarray data using nonparametric quadratic inference functions

Cites Work

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• Bootstrapping cluster analysis: Assessing the reliability of conclusions from microarray experiments
• A Convergence Theorem for the Fuzzy ISODATA Clustering Algorithms
• Well-Separated Clusters and Optimal Fuzzy Partitions
• Cluster analysis of gene expression dynamics

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