Clustering Plasmodium falciparum Genes to their Functional Roles Using k-means
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We developed recently a new and novel Metric
Matrics k-means (MMk-means) clustering algorithm to cluster
genes to their functional roles with a view of obtaining further
knowledge on many P. falciparum genes. To further pursue this
aim, in this study, we compare three different k-means
algorithms (including MMk-means) results from an in-vitro
microarray data (Le Roch et al., Science, 2003) with the
classification from an in-vivo microarray data (Daily et al.,
Nature, 2007) in other to perform a comparative functional
classification of P. falciparum genes and further validate the
effectiveness of our MMk-means algorithm. Results from this
study indicate that the resulting distribution of the comparison
of the three algorithms’ in vitro clusters against the in vivo
clusters are similar thereby authenticating our MMk-means
method and its effectiveness. However, Daily et al. claim that
the physiological state (the environmental stress response) of P.
falciparum in selected malaria-infected patients observed in one
of their clusters can not be found in any in-vitro clusters is not
true as our analysis reveal many in-vitro clusters representation
in this cluster.
Keywords
QA75 Electronic computers. Computer science