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Open AccessEssay

A Checklist for Successful Quantitative Live Cell Imaging in Systems Biology

National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA
Cells 2013, 2(2), 284-293; https://doi.org/10.3390/cells2020284
Received: 20 February 2013 / Revised: 3 April 2013 / Accepted: 15 April 2013 / Published: 29 April 2013
(This article belongs to the Special Issue Successes of Systems Biology and Future Challenges)
Mathematical modeling of signaling and gene regulatory networks has provided unique insights about systems behaviors for many cell biological problems of medical importance. Quantitative single cell monitoring has a crucial role in advancing systems modeling of molecular networks. However, due to the multidisciplinary techniques that are necessary for adaptation of such systems biology approaches, dissemination to a wide research community has been relatively slow. In this essay, I focus on some technical aspects that are often under-appreciated, yet critical in harnessing live cell imaging methods to achieve single-cell-level understanding and quantitative modeling of molecular networks. The importance of these technical considerations will be elaborated with examples of successes and shortcomings. Future efforts will benefit by avoiding some pitfalls and by utilizing the lessons collectively learned from recent applications of imaging in systems biology. View Full-Text
Keywords: quantitative microscopy; live cell imaging; fluorescent proteins; mathematical modeling; network models quantitative microscopy; live cell imaging; fluorescent proteins; mathematical modeling; network models
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MDPI and ACS Style

Sung, M.-H. A Checklist for Successful Quantitative Live Cell Imaging in Systems Biology. Cells 2013, 2, 284-293. https://doi.org/10.3390/cells2020284

AMA Style

Sung M-H. A Checklist for Successful Quantitative Live Cell Imaging in Systems Biology. Cells. 2013; 2(2):284-293. https://doi.org/10.3390/cells2020284

Chicago/Turabian Style

Sung, Myong-Hee. 2013. "A Checklist for Successful Quantitative Live Cell Imaging in Systems Biology" Cells 2, no. 2: 284-293. https://doi.org/10.3390/cells2020284

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