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Datta S., Datta, S. (2003), Comparisons and validation of statistical clustering techniques for microarray gene expression data, Bioinformatics, 19:459-466.

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A Comparative Study of Biological Distances for EST.. - Scott Hazelhurst Zsuzsanna (2003)   (Correct)

....different clustering though without a biological basis for interpreting these results, there is no way to decide which grouping is right and which is wrong. In their comparison of different clustering algorithms, Datta and Datta evaluate the algorithms based upon their internal consistency [5]. This gives some objective way of evaluating the algorithms, though the link to the real answer is indirect. Our methodology is most similar to that used in phylogenetic studies, where a phylogenetic tree is synthetically generated according to some evolutionary model, and then phylogenetic ....

S. Datta and S. Datta. Comparisons and validation of statistical clustering techniques for microarray data. Bioinformatics, 19(4):459--466, 2003.


Comparative Analysis of Clustering Methods for Gene Expression Data - Filho (2003)   (Correct)

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Datta S., Datta, S. (2003), Comparisons and validation of statistical clustering techniques for microarray gene expression data, Bioinformatics, 19:459-466.


Automatically Finding Good Clusters with Seed K-Means - Shin, Kang, Park (2003)   (Correct)

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Datta, S. and Datta, S., Comparisons and validation of statistical clustering techniques for microarray gene expression data, Bioinformatics, 19(4):459--466, 2003.


Comparative Analysis of Clustering Methods for Gene.. - Costa, de Carvalho, al. (2003)   (Correct)

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Datta S., Datta, S., Comparisons and validation of statistical clustering techniques for microarray gene expression data, Bioinformatics, 19:459-466, 2003.


A Method for Evaluating the Quality of String.. - Zimmermann, Liptak.. (2004)   (Correct)

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S. Datta and S. Datta. Comparisons and validation of statistical clustering techniques for microarray data. Bioinformatics, 19(4):459--466, 2003.

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