Abstract
This work investigates the behavior of two different clustering algorithms, with two proximity measures, in terms of the contents of the partitions obtained with them. An analysis of how the classes are separated by these algorithms, as different numbers of clusters are generated, is also presented. A discussion on the use of these information in the identification of special cases for further analysis by biologists is presented.
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© 2005 Springer-Verlag Berlin Heidelberg
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Faceli, K., de Carvalho, A.C.P.L.F., de Souto, M.C.P. (2005). Evaluation of the Contents of Partitions Obtained with Clustering Gene Expression Data. In: Setubal, J.C., Verjovski-Almeida, S. (eds) Advances in Bioinformatics and Computational Biology. BSB 2005. Lecture Notes in Computer Science(), vol 3594. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11532323_8
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DOI: https://doi.org/10.1007/11532323_8
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-28008-8
Online ISBN: 978-3-540-31861-3
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