Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, USA.
Computational Biology Department, Carnegie Mellon University, Pittsburgh, PA, USA.
Methods Mol Biol. 2024;2800:231-244. doi: 10.1007/978-1-0716-3834-7_16.
In this chapter, we describe protocols for using the CellOrganizer software on the Jupyter Notebook platform to analyze and model cell and organelle shape and spatial arrangement. CellOrganizer is an open-source system for using microscope images to learn statistical models of the structure of cell components and how those components are organized relative to each other. Such models capture the statistical variation in the organization of cellular components by jointly modeling the distributions of their number, shape, and spatial distributions. These models can be created for different cell types or conditions and compared to reflect differences in their spatial organizations. The models are also generative, in that they can be used to synthesize new cell instances reflecting what a model learned and to provide well-structured cell geometries that can be used for biochemical simulations.
在本章中，我们将描述在 Jupyter Notebook 平台上使用 CellOrganizer 软件的协议，以分析和模拟细胞和细胞器的形状和空间排列。CellOrganizer 是一个用于使用显微镜图像学习细胞成分结构的统计模型以及这些成分如何相互组织的开源系统。这些模型通过联合建模它们的数量、形状和空间分布的分布来捕获细胞成分组织的统计变化。可以为不同的细胞类型或条件创建这些模型，并进行比较以反映其空间组织的差异。这些模型也是生成性的，因为它们可以用于合成反映模型所学内容的新细胞实例，并提供可用于生化模拟的结构良好的细胞几何形状。
