Mars, a molecule archive suite for reproducible analysis and reporting of single-molecule properties from bioimages

Mars, a molecule archive suite for reproducible analysis and reporting of single-molecule properties from bioimages
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Mars,一个分子档案套件,用于对生物图像中的单分子特性进行可重复分析和报告

DOI:
10.1101/2021.11.26.470105
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发表时间:
2021
期刊:
影响因子:
7.7
通讯作者:
K. Duderstadt
K. Duderstadt
中科院分区:
生物学1区
文献类型:
--
作者:
Nadia M. Huisjes;Thomas M Retzer;Matthias J. Scherr;Rohit Agarwal;L. Rajappa;Barbara Safaric;A. Minnen;K. Duderstadt

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新成像方法的快速发展正在产生更大和更复杂的数据集,揭示单个细胞和生物分子的时间演变。特别是单分子技术,提供了在复杂的多阶段分子途径中获得稀有中间体的途径。然而,处理这些信息丰富的数据集的标准很少,给更广泛的传播带来了挑战。在这里,我们介绍了Mars,一个用于存储和处理生物分子图像衍生特性的开源平台。玛氏提供用Java编写的Fiji/ImageJ2命令,用于常见的单分子分析任务,使用分子存档架构,可轻松适应复杂的多步骤分析工作流程。涉及分子跟踪、多通道荧光成像和力谱的三种不同工作流程展示了分析应用的范围。用JavaFX编写的全面图形用户界面通过提供图表、标记、区域突出显示、可编写脚本的仪表板和交互式图像视图来增强生物分子特征探索。ImageJ2的互操作性确保了Molecule Archives可以在多个环境中轻松打开,包括使用PyImageJ编写的Python环境,用于交互式脚本和可视化。Mars为图像衍生属性的可重复分析提供了灵活的解决方案,通过开放的数据格式促进了新生物现象的发现和定量分类。
The rapid development of new imaging approaches is generating larger and more complex datasets revealing the time evolution of individual cells and biomolecules. Single-molecule techniques, in particular, provide access to rare intermediates in complex, multistage molecular pathways. However, few standards exist for processing these information-rich datasets, posing challenges for wider dissemination. Here, we present Mars, an open-source platform for storing and processing image-derived properties of biomolecules. Mars provides Fiji/ImageJ2 commands written in Java for common single-molecule analysis tasks using a Molecule Archive architecture that is easily adapted to complex, multistep analysis workflows. Three diverse workflows involving molecule tracking, multichannel fluorescence imaging, and force spectroscopy, demonstrate the range of analysis applications. A comprehensive graphical user interface written in JavaFX enhances biomolecule feature exploration by providing charting, tagging, region highlighting, scriptable dashboards, and interactive image views. The interoperability of ImageJ2 ensures Molecule Archives can easily be opened in multiple environments, including those written in Python using PyImageJ, for interactive scripting and visualization. Mars provides a flexible solution for reproducible analysis of image-derived properties, facilitating the discovery and quantitative classification of new biological phenomena with an open data format accessible to everyone.
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