计算机科学
蛋白质亚细胞定位预测
亚像素渲染
人工智能
过程(计算)
插件
亚细胞定位
计算生物学
计算机视觉
模式识别(心理学)
数据挖掘
生物系统
生物
细胞生物学
细胞质
像素
基因
操作系统
程序设计语言
生物化学
作者
Adrien Ducret,Ellen M. Quardokus,Yves V. Brun
出处
期刊:Nature microbiology
日期:2016-06-20
卷期号:1 (7)
被引量:713
标识
DOI:10.1038/nmicrobiol.2016.77
摘要
Single-cell analysis of bacteria and subcellular protein localization dynamics has shown that bacteria have elaborate life cycles, cytoskeletal protein networks and complex signal transduction pathways driven by localized proteins. The volume of multidimensional images generated in such experiments and the computation time required to detect, associate and track cells and subcellular features pose considerable challenges, especially for high-throughput experiments. There is therefore a need for a versatile, computationally efficient image analysis tool capable of extracting the desired relationships from images in a meaningful and unbiased way. Here, we present MicrobeJ, a plug-in for the open-source platform ImageJ1. MicrobeJ provides a comprehensive framework to process images derived from a wide variety of microscopy experiments with special emphasis on large image sets. It performs the most common intensity and morphology measurements as well as customized detection of poles, septa, fluorescent foci and organelles, determines their subcellular localization with subpixel resolution, and tracks them over time. Because a dynamic link is maintained between the images, measurements and all data representations derived from them, the editor and suite of advanced data presentation tools facilitates the image analysis process and provides a robust way to verify the accuracy and veracity of the data. MicrobeJ is an open-source ImageJ plug-in for the detection and quantitative analysis of bacterial cells.
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