In this paper, we consider six clustering algorithms (of various flavors!) and evaluate their performances on a well-known publicly available microarray data�...
Mar 20, 2015 � Comparison and Validation of Statistical Clustering Techniques for Microarray Gene Expression Data. April 2003; Bioinformatics 19(4):459-66. 19�...
Comparisons and validation of statistical clustering techniques for microarray gene expression data � Figures and Tables � Topics � 402 Citations � 26 References�...
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Here we quantify the performance of a given unsupervised clustering algorithm applied to a given microarray study in terms of its ability to produce�...
Oct 1, 2006 � Our results show that tight clustering and model-based clustering consistently outperform other clustering methods both in simulated and real�...
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Our analysis provides deep insight to the complicated gene clustering problem of expression profile and serves as a practical guideline for routine microarray�...
We applied several cluster validation measures to evaluate the performance of clustering algorithms for analyzing microarray gene expression data, including�...
This study's primary goal is to compare the effectiveness of various clustering methods while grouping microarray data both with and without outliers. Six�...
Many clustering techniques have been proposed for the analysis of gene expression data obtained from microarray experiments.
Aug 31, 2006 � In this paper, we introduce two performance measures for evaluating the results of a clustering algorithm in its ability to produce biologically meaningful�...