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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. Abstract

The 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.

I.Elbatal, "Kumaraswamy Generalized Linear Failure Rate Distribution", Indian Journal of Computational and Applied Mathematics, vol. 1, issue 1, pp. 61-78, 2013. kumaraswamy_generalized_linear.pdf
Abdelmoezz, S., and S. M. Mohamed, "The Kumaraswamy Lindley Regression Model with Application on the Egyptian Stock Exchange", JURNAL MATEMATIKA, STATISTIKA DAN KOMPUTASI (JMSK), vol. 18, issue 1, pp. 1-11, 2021. the_kumaraswamy_lindley_regression_model.pdf
Abdelmoezz, S., and S. M. Mohamed, "The Kumaraswamy Lindley Regression Model with Application on the Egyptian Stock Exchange", Jurnal Matematika, Statistika & Komputasi, vol. 18, issue 1, pp. 1-11, 2021. the_kumaraswamy_lindley_regression_model.pdf
Aryal, G., and I. Elbatal, "Kumaraswamy Modified Inverse Weibull Distribution: Theory and Application", Applied Mathematics & Information Sciences, vol. 9, issue 2, pp. 651-660, 2015. kumaraswamy_modified_inverse_weibull_distribution.pdf
Aryal, G., and I. Elbatal, "Kumaraswamy Modified Inverse Weibull Distribution: Theory and Application", Applied Mathematics & Information Sciences, vol. 9, issue 2, pp. 651-660, 2015.
Aryal, G., and I. Elbatal, "Kumaraswamy Modified Inverse Weibull Distribution: Theory and Application", Applied Mathematics & Information Sciences, vol. 9, issue 2, pp. 651-660, 2015. kumaraswamy_modified_inverse_weibull_distribution.pdf
eLsherpieny, E. A., and M. M. Elsehetry, "Kumaraswamy Type I Half Logistic Family of Distributions with Applications", Gazi University Journal of Science, vol. 32, issue 1, pp. 333-349, 2019.
Hassan, A. S., and M. Elgarhy, "Kumaraswamy Weibull-Generated Family of Distributions with Applications", Advances and Application in Statistics, vol. 48, issue 3, pp. 205-239, 2016. as048030205.pdf
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. the_kumaraswamy_transmuted_exponentiated_modified_weibull_distribution.pdf
Ashour, S. K., and M. A. L. Wahed, "Kummer Beta –Weibull Geometric Distribution, A New Generalization of Beta -Weibull Geometric Distribution", International Journal of Sciences: Basic and Applied Research (IJSBAR), vol. 16, issue 2, pp. 258-273, 2014. 2421-5475-1-pb.pdf