A comparison between the performance of Weibull and Log-logistic Aging Models on Saccharomyces cerevisiae lifespan data

Year 2020, , 123 - 132, 23.03.2020

Emine Güven

https://doi.org/10.35193/bseufbd.600693

Cited By: 1

Abstract

Empirical
lifespan datasets are often studied with the best-fitted mathematical model for
aging. In this study, we focus our attention to the budding yeast S. cerevisiae lifespan and the determination
of the best-fitted model of aging. We investigate the influence of model
selection in yeast lifespan datasets and the fitting outcomes of the
two-parameter Weibull (WE) and Log-logistic (LL) models of aging. Both of these
models are commonly studied and implemented in aging research. They show
similar tendency as a survival function that they correspond
to mortality rates that increase, and then decrease, with time. Studies so far
has been usually done with medflies,
Drosophila, house flies, flour beetles, and humans with these models. Different
than previous research, we focus our attention on the influence of fitting
results and calibrations on empirical lifespan data samples. As expected both
of the models could be used as a substitute of each other. However, we also find
WE model fits the yeast lifespan data significantly better than LL model with
an R² = 0.86.  This finding is
especially important in yeast aging study because of typically survival models
are applied and therefore one can see which model fits the yeast data best. In
this article, comparisons are done and 
developed and the potential of the approach is demonstrated with a model
comparison of yeast replicative lifespan datasets of the laboratory BY4741 and
BY4742 wildtype reference strains. Our study highlights that interpreting model
fitting results of experimental lifespans should take model selection and
resulted variation into account.

Keywords

the Weibull Model, the Log-logistic Model, survival analysis, aging, yeast

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