Clustering of Human Endogenous Retrovirus Sequences with Median Self-Organizing Map

Mutual relationships of human endogenous retroviruses (HERVs) and their similarities to other DNA elements are studied in this paper. We demonstrate that a completely data-driven grouping is able to reflect same kinds of relationships as more traditional biological classifications and phylogenetic taxonomies. The clusters and their visualization were computed with the Median Self-Organizing Map algorithm of pairwise FASTA-based distances. The wholesequence distances are able to distinguish between the different known types of endogenous elements, and exogenous retroviruses. The HERVs become grouped meaningfully.

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