Making microscopy count: quantitative light microscopy of dynamic processes in living plants.
Making microscopy count: quantitative light microscopy of dynamic processes in living plants.
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让显微镜发挥作用：活体植物动态过程的定量光学显微镜。
DOI：
10.1111/jmi.12403
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发表时间：
2016
影响因子：
2
通讯作者：
Fricker MD
中科院分区：
文献类型：
--
作者：
Fricker MD
细胞理论已经正式达到350岁，因为“细胞”一词在生物学背景下的第一次使用可以追溯到罗伯特·胡克在他的历史性出版物“Micrographia：or some physiological definitions of minute bodies”中描述的植物材料。2015年皇家显微学会植物显微镜会议是对胡克发起的研究流的庆祝，以了解在亚细胞尺度上植物细胞的功能和形式是如何产生的。大部分的工作提出，并授予荣誉奖学金，反映了先进的应用生物成像信息学提取定量数据的显微照片，揭示动态分子过程驱动细胞生长和生理。该领域已经从以多种模式收集许多像素发展到将这些测量与具有生物学意义的对象或特征相关联。额外的复杂性涉及对象识别，它利用了计算机科学和统计学的不同类型的专业知识，而这些知识通常是生物学家无法理解的。有许多有用的工具和方法正在开发中，但我们现在需要更多的跨学科交流，以有效地使用它们。在这篇评论中，我们将展示这场安静的革命如何为任何个人计算机用户提供工具。我们还讨论了量化算法鲁棒性这一经常被忽视的问题，以及通过将生物传感器生成的生理信息与目标检测和跟踪相结合所提供的令人兴奋的可能性。
Cell theory has officially reached 350 years of age as the first use of the word ‘cell’ in a biological context can be traced to a description of plant material by Robert Hooke in his historic publication ‘Micrographia: or some physiological definitions of minute bodies’. The 2015 Royal Microscopical Society Botanical Microscopy meeting was a celebration of the streams of investigation initiated by Hooke to understand at the subcellular scale how plant cell function and form arises. Much of the work presented, and Honorary Fellowships awarded, reflected the advanced application of bioimaging informatics to extract quantitative data from micrographs that reveal dynamic molecular processes driving cell growth and physiology. The field has progressed from collecting many pixels in multiple modes to associating these measurements with objects or features that are meaningful biologically. The additional complexity involves object identification that draws on a different type of expertise from computer science and statistics that is often impenetrable to biologists. There are many useful tools and approaches being developed, but we now need more interdisciplinary exchange to use them effectively. In this review we show how this quiet revolution has provided tools available to any personal computer user. We also discuss the oft‐neglected issue of quantifying algorithm robustness and the exciting possibilities offered through the integration of physiological information generated by biosensors with object detection and tracking.