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YeastRGB:比较细胞和文库中酵母蛋白的丰度和定位。

YeastRGB: comparing the abundance and localization of yeast proteins across cells and libraries.

机构信息

Department of Structural Biology, Weizmann Institute of Science, Rehovot, Israel.

Department of Molecular Genetics, Weizmann Institute of Science, Rehovot, Israel.

出版信息

Nucleic Acids Res. 2019 Jan 8;47(D1):D1245-D1249. doi: 10.1093/nar/gky941.

Abstract

The ability to measure the abundance and visualize the localization of proteins across the yeast proteome has stimulated hypotheses on gene function and fueled discoveries. While the classic C' tagged GFP yeast library has been the only resource for over a decade, the recent development of the SWAT technology has led to the creation of multiple novel yeast libraries where new-generation fluorescent reporters are fused at the N' and C' of open reading frames. Efficient access to these data requires a user interface to visualize and compare protein abundance, localization and co-localization across cells, strains, and libraries. YeastRGB (www.yeastRGB.org) was designed to address such a need, through a user-friendly interface that maximizes informative content. It employs a compact display where cells are cropped and tiled together into a 'cell-grid.' This representation enables viewing dozens of cells for a particular strain within a display unit, and up to 30 display units can be arrayed on a standard high-definition screen. Additionally, the display unit allows users to control zoom-level and overlay of images acquired using different color channels. Thus, YeastRGB makes comparing abundance and localization efficient, across thousands of cells from different strains and libraries.

摘要

能够测量酵母蛋白质组中蛋白质的丰度并可视化其定位,这激发了人们对基因功能的假设,并推动了新发现。虽然经典的 C' 标记 GFP 酵母文库已经是十年来唯一的资源,但最近 SWAT 技术的发展导致了多个新型酵母文库的创建,其中新一代荧光报告基因融合在开放阅读框的 N' 和 C'。高效访问这些数据需要一个用户界面,以可视化和比较细胞、菌株和文库之间的蛋白质丰度、定位和共定位。YeastRGB(www.yeastRGB.org)旨在通过用户友好的界面来满足这一需求,该界面最大限度地提高了信息量。它采用了一种紧凑的显示方式,将细胞裁剪并拼贴在一起形成“细胞网格”。这种表示形式可以在一个显示单元中查看特定菌株的数十个细胞,并且可以在标准高清屏幕上排列多达 30 个显示单元。此外,显示单元允许用户控制使用不同颜色通道获取的图像的缩放级别和叠加。因此,YeastRGB 使得比较不同菌株和文库中数千个细胞的丰度和定位变得高效。

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