Ais: streamlining segmentation of cryo-electron tomography datasets

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Abstract

Segmentation is a critical data processing step in many applications of cryo-electron tomography. Downstream analyses, such as subtomogram averaging, are often based on segmentation results, and are thus critically dependent on the availability of open-source software for accurate as well as high-throughput tomogram segmentation. There is a need for more user-friendly, flexible and comprehensive segmentation software that offers an insightful overview of all steps involved in preparing automated segmentations. Here, we present Ais: a dedicated tomogram segmentation package that is geared towards both high performance and accessibility, available at<ext-link xmlns:xlink="http://www.w3.org/1999/xlink" ext-link-type="uri" xlink:href="http://www.github.com/bionanopatterning/Ais">github.com/bionanopatterning/Ais</ext-link>. In this report, we demonstrate two common processing steps that can be greatly accelerated with Ais: particle picking for subtomogram averaging, and generating many-feature models of cellular architecture based onin situtomography data. Featuring comprehensive annotation, segmentation, and rendering functionality, as well as an open repository for trained models at<ext-link xmlns:xlink="http://www.w3.org/1999/xlink" ext-link-type="uri" xlink:href="http://aiscryoet.org">aiscryoet.org</ext-link>, we hope that Ais will help accelerate research and dissemination of data involving cryoET.

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