干细胞时空动力学的统计和数学建模
Statistical and mathematical modeling of spatiotemporal dynamics of stem cells
摘要：
统计和数学建模对于描述，解释，比较和预测复杂生物系统的行为至关重要，包括骨髓环境中造血干细胞和祖细胞的组织。目前高分辨率和活细胞成像数据的突出为研究这些细胞在其干细胞龛内的时空动态提供了前所未有的机会，并更多地了解异常但未受干扰的正常造血。然而，这需要对细胞的空间和时间行为以及与其微环境的相互作用进行仔细的定量统计分析。此外，这种量化是构建假设驱动的数学模型的先决条件，这些模型可以通过生成可以直接与实验观测进行比较的时空动态来提供机械解释。在这里，我们提供了一个简要的概述，在分析细胞的空间分布，细胞运动，细胞形状和细胞谱系的统计方法。我们还描述了基于细胞的建模形式主义，使研究人员能够模拟紧急行为的基础上，一套假设的机制在多细胞系统。总之，这些方法为造血干细胞和祖细胞的时空行为的分析和综合研究提供了定量工作流程。
英文摘要：
Statistical and mathematical modeling are crucial to describe, interpret, compare and predict the behavior of complex biological systems including the organization of hematopoietic stem and progenitor cells in the bone marrow environment. The current prominence of high-resolution and live-cell imaging data provides an unprecedented opportunity to study the spatiotemporal dynamics of these cells within their stem cell niche and learn more about aberrant, but also unperturbed, normal hematopoiesis. However, this requires careful quantitative statistical analysis of the spatial and temporal behavior of cells and the interaction with their microenvironment. Moreover, such quantification is a prerequisite for the construction of hypothesis-driven mathematical models that can provide mechanistic explanations by generating spatiotemporal dynamics that can be directly compared to experimental observations. Here, we provide a brief overview of statistical methods in analyzing spatial distribution of cells, cell motility, cell shapes and cellular genealogies. We also describe cell- based modeling formalisms that allow researchers to simulate emergent behavior in a multicellular system based on a set of hypothesized mechanisms. Together, these methods provide a quantitative workflow for the analytic and synthetic study of the spatiotemporal behavior of hematopoietic stem and progenitor cells.
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