在细胞可塑性模型中根据细胞比例确定细胞种群大小
Determining cell population size from cell fraction in cell plasticity models
AI总结：
针对仅有细胞类型相对频率而缺乏绝对计数的问题，提出基于随机种群模型的FOM与SOM矩方法，由细胞比例估计种群大小，其中SOM无需初始规模先验。
摘要：
量化细胞种群的大小对于理解生长、损伤修复和疾病进展等生物过程至关重要。实验数据通常以不同细胞类型的相对频率而非绝对细胞数的形式提供信息，这凸显了制定有效策略以从比例数据估计绝对细胞数量的必要性。为应对这一挑战，我们提出两种基于随机细胞种群模型的计算方法：一阶矩方法（FOM）和二阶矩方法（SOM）。这些方法利用随机模型的矩方程，明确建立了从细胞比例到细胞种群大小的数学映射。值得注意的是，我们的研究表明，SOM方法无需预先知道初始种群大小，这凸显了纳入细胞比例方差信息的效用。我们从不同角度分析了FOM和SOM方法的稳健性。此外，我们将FOM和SOM方法的应用扩展到细胞可塑性模型背景下的多种生物机制。我们的方法不仅有助于缓解在仅有比例数据可用于检测细胞种群大小时实验技术固有的局限性，还为利用细胞种群动态的随机特征来量化系统内不同生物量之间的相互作用提供了新的见解。
英文摘要：
Quantifying the size of cell populations is crucial for understanding biological processes such as growth, injury repair, and disease progression. Often, experimental data offer information in the form of relative frequencies of distinct cell types, rather than absolute cell counts. This emphasizes the need to devise effective strategies for estimating absolute cell quantities from fraction data. In response to this challenge, we present two computational approaches grounded in stochastic cell population models: the first-order moment method (FOM) and the second-order moment method (SOM). These methods explicitly establish mathematical mappings from cell fraction to cell population size using moment equations of the stochastic models. Notably, our investigation demonstrates that the SOM method obviates the requirement for a priori knowledge of the initial population size, highlighting the utility of incorporating variance details from cell proportions. The robustness of both the FOM and SOM methods was analyzed from different perspectives. Additionally, we extended the application of the FOM and SOM methods to various biological mechanisms within the context of cell plasticity models. Our methodologies not only assist in mitigating the inherent limitations of experimental techniques when only fraction data is available for detecting cell population size, but they also offer new insights into utilizing the stochastic characteristics of cell population dynamics to quantify interactions between different biomasses within the system.
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