Finding Bioelectronics Correlations in Retro-transcribing Viral Proteomic Sequences Using an Evolutionary Clustering Technique

A cluster analysis on a set of Retro-Transcribing viral proteomic sequences is described in this paper. A Lysine-Arginine concentration vector is calculated from the sequences and analyzed to identify correlations among species. The computational strategy is based on the K-Means algorithm to partition the data into disjoint sets of points. A search method based on Evolutionary Programming is incorporated, in order to optimize the cluster structures. Experimental results show a number of interesting and unexpected similarities. These similarities could suggest bioelectronics relationships, in the context of the electronic mobility theory.