@article {67989,
	title = {Quantifying Molecular Dynamics within Complex Cellular Morphologies using LLSM-FRAP.},
	journal = {Small Methods},
	year = {2022},
	month = {2022 Jun 01},
	pages = {e2200149},
	abstract = {<p>Quantifying molecular dynamics within the context of complex cellular morphologies is essential toward understanding the inner workings and function of cells. Fluorescence recovery after photobleaching (FRAP) is one of the most broadly applied techniques to measure the reaction diffusion dynamics of molecules in living cells. FRAP measurements typically restrict themselves to single-plane image acquisition within a subcellular-sized region of interest due to the limited temporal resolution and undesirable photobleaching induced by 3D fluorescence confocal or widefield microscopy. Here, an experimental and computational pipeline combining lattice light sheet microscopy, FRAP, and numerical simulations, offering rapid and minimally invasive quantification of molecular dynamics with respect to 3D cell morphology is presented. Having the opportunity to accurately measure and interpret the dynamics of molecules in 3D with respect to cell morphology has the potential to reveal unprecedented insights into the function of living cells.</p>
},
	issn = {2366-9608},
	doi = {10.1002/smtd.202200149},
	author = {Colin-York, Huw and Heddleston, John and Wait, Eric and Karedla, Narain and DeSantis, Michael and Khuon, Satya and Chew, Teng-Leong and Sbalzarini, Ivo F and Fritzsche, Marco}
}
@article {64903,
	title = {Practical considerations in particle and object tracking and analysis.},
	journal = {Current Protocols in Cell Biology},
	volume = {83},
	year = {2019},
	month = {2019 Jun 01},
	pages = {e88},
	abstract = {<p>The rapid advancement of live-cell imaging technologies has enabled biologists to generate high-dimensional data to follow biological movement at the microscopic level. Yet, the "perceived" ease of use of modern microscopes has led to challenges whereby sub-optimal data are commonly generated that cannot support quantitative tracking and analysis as a result of various ill-advised decisions made during image acquisition. Even optimally acquired images often require further optimization through digital processing before they can be analyzed. In writing this article, we presume our target audience to be biologists with a foundational understanding of digital image acquisition and processing, who are seeking to understand the essential steps for particle/object tracking experiments. It is with this targeted readership in mind that we review the basic principles of image-processing techniques as well as analysis strategies commonly used for tracking experiments. We conclude this technical survey with a discussion of how movement behavior can be mathematically modeled and described. {\textcopyright} 2019 by John Wiley \&amp; Sons, Inc.</p>
},
	issn = {1934-2616},
	doi = {10.1002/cpcb.88},
	author = {Aaron, Jesse and Wait, Eric and DeSantis, Michael and Chew, Teng-Leong}
}
