Predição e caracterização de ilhas genômicas em bactérias do gênero Mycoplasmas, utilizando o método de clusterização Mean Shift.

Abstract

Costs with genetic sequencing have been greatly reduced in the past few years, leading to an increase in Mycoplasma species sequenced. The availability of numerous structural genomic data provided the exploitation of such information, especially for Genomic Islands (GIs). GIs are regions of the bacterial genome that may contain genes acquired by horizontal transfers from other organisms, which can confer adaptations, such as virulence and antibiotic resistance. Detection and characterization of these regions allows researchers to identify genes responsible for these adaptations and develop new vaccines and antibiotics. Current methods for GIs detection require improvement. This study proposes an alternative method for detection of Mycoplasma GIs, the Mean Shift clustering method, and characterization of these GIs, gathering the proteins by a phylogenetic classification of Proteins Encoded in Clusters of Orthologous Groups (COGs).