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EVOW
2006
Springer

Hierarchical Clustering, Languages and Cancer

10 years 5 months ago
Hierarchical Clustering, Languages and Cancer
In this paper, we introduce a novel objective function for the hierarchical clustering of data from distance matrices, a very relevant task in Bioinformatics. To test the robustness of the method, we test it in two areas: (a) the problem of deriving a phylogeny of languages and (b) subtype cancer classification from microarray data. For comparison purposes, we also consider both the use of ultrametric trees (generated via a two-phase evolutionary approach that creates a large number of hypothesis trees, and then takes a consensus), and the best-known results from the literature. We used a dataset of measured 'separation time' among 84 Indo-European languages. The hierarchy we produce agrees very well with existing data about these languages across a wide range of levels, and it helps to clarify and raise new hypothesis about the evolution of these languages. Our method also generated a classification tree for the different cancers in the NCI60 microarray dataset (comprising g...
Pritha Mahata, Wagner Costa, Carlos Cotta, Pablo M
Added 22 Aug 2010
Updated 22 Aug 2010
Type Conference
Year 2006
Where EVOW
Authors Pritha Mahata, Wagner Costa, Carlos Cotta, Pablo Moscato
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