Akhter, S., R. K. Aziz, M. O. N. A. T. KASHEF, E. S. Ibrahim, B. Bailey, and R. A. Edwards,
"Kullback Leibler divergence in complete bacterial and phage genomes.",
PeerJ, vol. 5, pp. e4026, 2017.
AbstractThe amino acid content of the proteins encoded by a genome may predict the coding potential of that genome and may reflect lifestyle restrictions of the organism. Here, we calculated the Kullback-Leibler divergence from the mean amino acid content as a metric to compare the amino acid composition for a large set of bacterial and phage genome sequences. Using these data, we demonstrate that (i) there is a significant difference between amino acid utilization in different phylogenetic groups of bacteria and phages; (ii) many of the bacteria with the most skewed amino acid utilization profiles, or the bacteria that host phages with the most skewed profiles, are endosymbionts or parasites; (iii) the skews in the distribution are not restricted to certain metabolic processes but are common across all bacterial genomic subsystems; (iv) amino acid utilization profiles strongly correlate with GC content in bacterial genomes but very weakly correlate with the G+C percent in phage genomes. These findings might be exploited to distinguish coding from non-coding sequences in large data sets, such as metagenomic sequence libraries, to help in prioritizing subsequent analyses.
Al-Babtain, A., A. A. Fattah, A. - H. N. Ahmed, and F. Merovci,
"The Kumaraswamy-transmuted exponentiated modified Weibull distribution",
Communications in Statistics - Simulation and Computation, vol. 46, issue 5, pp. 3812-3832, 2017.