An atlas of whole cells and tissues that sheds light on how the organelles in a cell work together was published today in Nature. The atlas is enabled by computer algorithms that can automatically identify some 30 different kinds of organelles and other structures in super high-resolution images of entire cells. 

The detail in these images would be nearly impossible to parse by hand throughout the entire cell, says Aubrey Weigel, from Howard Hughes Medical Institute’s Janelia Research Campus who led the project team, called COSEM (for Cell Organelle Segmentation in Electron Microscopy). The data for just one cell is made up of tens of thousands of images; tracing all a cell’s organelles through that collection of pictures would take one person more than 60 years. But the new algorithms make it possible to map an entire cell in hours, rather than years. 

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“By using machine learning to process the data, we felt we could revisit the canonical view of a cell,” Weigel says. 

In addition to two companion articles in Nature, Janelia scientists also released a data portal, OpenOrganelle, where anyone can access the datasets and tools they’ve created.