Tight clustering for large datasets with an application to gene expression data

Author:

Karmakar Bikram,Das Sarmistha,Bhattacharya Sohom,Sarkar Rohan,Mukhopadhyay Indranil

Publisher

Springer Science and Business Media LLC

Subject

Multidisciplinary

Reference35 articles.

1. Eisen, M. B., Spellman, P. T., Brown, P. O. & Botstein, D. Cluster analysis and display of genome-wide expression patterns. Proc. Natl. Acad. Sci. 95, 14863–14868 (1998).

2. MacQueen, J. Some methods for classification and analysis of multivariate observations. Proc Fifth Berkeley Sympos. Math. Stat. and Probab. (Berkeley, Calif., 1965/66), Vol. I: Statistics. 281–297 (1967).

3. Kaufman, L. & Rousseeuw, P. J. Finding Groups in Data: An Introduction to Cluster Analysis. John Wiley & Sons, Inc., first edition (2008).

4. Kohonen, T. Self-organizing maps. Volume 30 of Springer Series in Information Sciences. Springer-Verlag, Berlin, second edition (1997).

5. Tamayo, P. et al. Interpreting patterns of gene expression with self-organizing maps: Methods and application to hematopoietic differentiation. Proc. Natl. Acad. Sci. 96, 2907–2912 (1999).

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