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Clustering Plasmodium falciparum Genes to their Functional Roles Using k-means

Osamor, V. C. and Adebiyi, E. F. and Doumbia, Seydou (2010) Clustering Plasmodium falciparum Genes to their Functional Roles Using k-means. International Journal of Engineering and Technology, 2 (2). pp. 215-225. ISSN 1793-8236

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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.

Item Type: Article
Uncontrolled Keywords: clustering algorithm; effectiveness; functional classification; malaria parasite; genes; in-vivo; in-vitro; microarray. I
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Faculty of Engineering, Science and Mathematics > School of Electronics and Computer Science
Depositing User: Mrs Patricia Nwokealisi
Date Deposited: 30 Mar 2022 16:05
Last Modified: 30 Mar 2022 16:05

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