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Taking into account an evolutionary model of mutations in term of Levy Fights that was previously constructed, we designed an algorithm to reproduce the evolutionary dynamics of the Long-Term Evolution Experiment (LTEE) with E. Coli bacteria. The algorithm enables us to simulate mutations under natural selection conditions. The results of simulations on competition of clones, mean fitness, etc., are compared with experimental data. We attained to reproduce the behavior of the mean fitness of the bacteria cultures, get our own interpretations and more tuned descriptions of some phenomena taking part within the experiment, such as fixation and drift processes, clonal interference and epistasis.
We revisit the model by Wiser, Ribeck, and Lenski (Science textbf{342} (2013), 1364--1367), which describes how the mean fitness increases over time due to beneficial mutations in Lenskis long-term evolution experiment. We develop the model further b
The unwelcome evolution of malignancy during cancer progression emerges through a selection process in a complex heterogeneous population structure. In the present work, we investigate evolutionary dynamics in a phenotypically heterogeneous populatio
Biological systems are typically highly open, non-equilibrium systems that are very challenging to understand from a statistical mechanics perspective. While statistical treatments of evolutionary biological systems have a long and rich history, exam
The world evolution of the Severe acute respiratory syndrome coronavirus 2 (SARS-Cov2 or simply COVID-19) led the World Health Organization to declare it a pandemic. The disease appeared in China in December 2019, and it has spread fast around the wo
The possibility of complicated dynamic behaviour driven by non-linear feedbacks in dynamical systems has revolutionized science in the latter part of the last century. Yet despite examples of complicated frequency dynamics, the possibility of long-te