Petabytes of increasingly complex and multidimensional live cell and tissue imaging data are generated every year. These videos hold large promise for understanding biology at a deep and fundamental level, as they capture single-cell and multicellular events occurring over time and space. However, the current modalities for analysis and mining of these data are scattered and user-specific, preventing more unified analyses from being performed over different datasets and obscuring possible scientific insights. Here, we propose a unified pipeline for storage, segmentation, analysis, and statistical parametrization of live cell imaging datasets.

中文翻译：

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迈向对生物时间过程数据的“端到端”分析和理解。

每年都会产生数 PB 的日益复杂和多维的活细胞和组织成像数据。这些视频为深入和基础层面理解生物学提供了巨大的希望，因为它们捕捉了随时间和空间发生的单细胞和多细胞事件。然而，当前分析和挖掘这些数据的方式是分散的和特定于用户的，阻碍了对不同数据集进行更统一的分析，并掩盖了可能的科学见解。在这里，我们提出了一个用于活细胞成像数据集的存储、分割、分析和统计参数化的统一管道。