Simulación de diferentes distribuciones de edades para el análisis de la curva de envejecimiento de una población de células “S. cerevisiae”.

Abstract

Aging is a complex biological process in which many are involved; this is mainly based on the change of the functioning of cells over time. Some of these changes can bring about different types of diseases, such as heart disease, degenerative disease, or cancer. Preventing and finding some of the major causes is why the study of aging has become significant in recent years. This research is mainly carried out on yeast cells with the help of new microfluidic devices. These devices track a group of cells and monitor certain physiological changes over time. One of the results of these studies is the aging curve. When these curves are made, some information can be omitted since in certain devices, it cannot be guaranteed that the cells studied are virgin. Therefore, it is difficult to know with certainty whether the curve that was made corresponds to the true behavior of the aging of the population. Therefore, the present work seeks to perform a series of simulations, in which different initial age distributions are found, to observe the various aging curves that may be presented, in order to compare them with experimental data and curves and to be able to provide more information about them. First, we proposed a simplified population growth model (synchronous), then another more complex model (asynchronous) was proposed, considering that the replication time for each cell is different. Thus make the simulation as close as possible to the growth behavior of a cell population. The simulations were performed in the Python programming language. At the end, simulated aging curves are compared, with experimental curves of 3 articles, to see in which generation the curves are best adjusted.