OpenCell on AWS

The OpenCell project is a proteome-scale effort to measure the localization and interactions of human proteins using high-throughput genome engineering to endogenously tag thousands of proteins in the human proteome. This dataset consists of the raw confocal fluorescence microscopy images for all tagged cell lines in the OpenCell library. These images can be interpreted both individually, to determine the localization of particular proteins of interest, and in aggregate, by training machine learning models to classify or quantify subcellular localization patterns.

OpenCell 项目是一项针对人类蛋白质组进行定位和相互作用测量的蛋白质组规模努力，该努力通过高通量基因组工程对数千个蛋白质进行内源标记。本数据集包含 OpenCell 库中所有标记细胞系的原始共聚焦荧光显微镜图像。这些图像既可以单独解读，以确定特定蛋白质的兴趣定位，也可以通过训练机器学习模型来分类或量化亚细胞定位模式的方式进行汇总分析。