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Computational analysis of spatiotemporal molecular hierarchy in single live cells
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作者 Shaoying Lu Jihye Seong +4 位作者 Yi Wang Shiou-chi Chang john paul eichorst Mingxing Ouyang Yingxiao Wang 《医用生物力学》 EI CAS CSCD 北大核心 2013年第S1期55-55,共1页
Genetically encoded biosensors based on fluorescence resonance energy transfer(FRET)have been widely applied to visualize the molecular activity in live cells with high spatiotemporal resolution.The enormous amount of... Genetically encoded biosensors based on fluorescence resonance energy transfer(FRET)have been widely applied to visualize the molecular activity in live cells with high spatiotemporal resolution.The enormous amount of video images and the complex dynamics of signaling events present tremendous challenges for data analysis and demand the development of intelligent and automated imaging analysis methods specifically envisioned for the studies of live cell imaging.We have developed a general correlative FRET imaging method(CFIM)to quantify the subcellular coupling between an enzymatic activity and a phenotypic response in live cells,e.g.at focal adhesions(FAs).CFIM quantitatively evaluated the cause-effect relation- 展开更多
关键词 visualize quantify FRET biosensors correlative INTELLIGENT quantitatively enormous AUTOMATED tremendous
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