A Bayesian Analysis of Plant DNA Length Distribution via κ-Statistics

Abstract

We report an analysis of the distribution of lengths of plant DNA (exons). Three species of Cucurbitaceae were investigated. In our study, we used two distinct κ distribution functions, namely, κ-Maxwellian and double-κ, to fit the length distributions. To determine which distribution has the best fitting, we made a Bayesian analysis of the models. Furthermore, we filtered the data, removing outliers, through a box plot analysis. Our findings show that the sum of κ-exponentials is the most appropriate to adjust the distribution curves and that the values of the κ parameter do not undergo considerable changes after filtering. Furthermore, for the analyzed species, there is a tendency for the κ parameter to lay within the interval (0.27;0.43).

The Scientific Contribution of the Kaniadakis Entropy to Nuclear Reactor Physics: A Brief Review

“…Given this considerable versatility, one can find several scientific papers that have applied the Kaniadakis-type deformed statistics. To illustrate this usefulness, one can cite works in astrophysics [ 6 ], cosmology [ 7 ], DNA analysis [ 8 ], quark–gluon plasma [ 9 ], game theory [ 10 ], error theory [ 11 ], information theory [ 12 ], random matrices [ 13 ], fractal systems [ 14 ], dusty-type plasmas [ 15 ], gravitational physics [ 16 , 17 ], epidemiology [ 18 ], Jeans instability of self-gravitating systems [ 19 ], and nuclear reactor physics [ 3 , 20 , 21 , 22 , 23 ].…”