The Effect of Gaussian Noise on Maximum Likelihood Fitting of Gompertz and Weibull Mortality Models with Yeast Lifespan Data
The Effect of Gaussian Noise on Maximum Likelihood Fitting of Gompertz and Weibull Mortality Models with Yeast Lifespan Data
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DOI：
10.1080/0361073x.2019.1586105
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发表时间：
2019-03-15
影响因子：
1.8
通讯作者：
Qin, Hong
中科院分区：
文献类型：
--
作者：
Guven, Emine;Akcay, Sevinc;Qin, Hong
背景/研究背景：经验寿命数据集通常使用最适合的衰老数学模型进行研究。在这里，我们研究了实验噪声如何影响最佳拟合老化模型的确定。我们研究了寿命数据集中高斯白噪声对老龄化研究中常用的双参数Gompertz和Weibull死亡率模型拟合结果的影响。方法：为了明确地证明高斯白噪声的影响，我们在加入白噪声的Gompertz和Weibull模型的基础上模拟了寿命。为了衡量白噪声对模型拟合的影响，我们为Weibull和Gompertz模型拟合的最大对数似然之间的差异定义了一个单一指数，。然后，我们将该方法应用于实验室BY4741和BY4742野生型参考菌株的实验复制寿命数据集。结果：我们系统地评估了高斯白噪声如何影响基于最大似然的Gompertz和Weibull模型的比较。我们的对比研究表明，威布尔模型对高斯白噪声的容忍度一般高于Gompertz模型。噪声对模型拟合的影响对模型参数也很敏感。结论：高斯白噪声会影响酵母复制寿命老化模型的拟合。鉴于酵母的复制寿命很难测量，并且经常从不同的实验中汇总，我们的研究强调，解释模型拟合结果应该考虑实验程序的变化，最好的拟合模型不一定能提供更多的生物学见解。
Background/study context: Empirical lifespan data sets are often studied with the best-fitted mathematical model for aging. Here, we studied how experimental noises can influence the determination of the best-fitted aging model. We investigated the influence of Gaussian white noise in lifespan data sets on the fitting outcomes of two-parameter Gompertz and Weibull mortality models, commonly adopted in aging research. Methods: To un-equivocally demonstrate the effect of Gaussian white noises, we simulated lifespans based on Gompertz and Weibull models with added white noises. To gauge the influence of white noise on model fitting, we defined a single index, , for the difference between the maximal log-likelihoods of the Weibull and Gompertz model fittings. We then applied the approach using experimental replicative lifespan data sets for the laboratory BY4741 and BY4742 wildtype reference strains. Results: We systematically evaluated how Gaussian white noise can influence the maximal likelihood-based comparison of the Gompertz and Weibull models. Our comparative study showed that the Weibull model is generally more tolerant to Gaussian white noise than the Gompertz model. The effect of noise on model fitting is also sensitive to model parameters. Conclusion: Our study shows that Gaussian white noise can influence the fitting of an aging model for yeast replicative lifespans. Given that yeast replicative lifespans are hard to measure and are often pooled from different experiments, our study highlights that interpreting model fitting results should take experimental procedure variation into account, and the best fitting model may not necessarily offer more biological insights.