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| Content Provider | World Health Organization (WHO)-Global Index Medicus |
|---|---|
| Author | Rollins, Geoffrey C. Bustamante, Carlos Pressé, Steve Shin, Jae Yen |
| Description | Author Affiliation: Rollins GC ( Department of Biochemistry and Biophysics, University of California, San Francisco, CA 94158); Shin JY ( Howard Hughes Medical Institute and.); Bustamante C ( Howard Hughes Medical Institute and Departments of Physics, Molecular and Cell Biology, and Chemistry, QB3 Institute, University of California, Berkeley, CA 94720); Pressé S ( Department of Physics, Indiana University-Purdue University Indianapolis, Indianapolis, IN 46202); |
| Abstract | Superresolution imaging methods--now widely used to characterize biological structures below the diffraction limit--are poised to reveal in quantitative detail the stoichiometry of protein complexes in living cells. In practice, the photophysical properties of the fluorophores used as tags in superresolution methods have posed a severe theoretical challenge toward achieving this goal. Here we develop a stochastic approach to enumerate fluorophores in a diffraction-limited area measured by superresolution microscopy. The method is a generalization of aggregated Markov methods developed in the ion channel literature for studying gating dynamics. We show that the method accurately and precisely enumerates fluorophores in simulated data while simultaneously determining the kinetic rates that govern the stochastic photophysics of the fluorophores to improve the prediction's accuracy. This stochastic method overcomes several critical limitations of temporal thresholding methods. |
| ISSN | 00278424 |
| e-ISSN | 10916490 |
| Journal | Proceedings of the National Academy of Sciences of the United States of America |
| Issue Number | 2 |
| Volume Number | 112 |
| Language | English |
| Publisher | National Academy of Sciences |
| Publisher Date | 2015-01-01 |
| Publisher Place | United States |
| Access Restriction | Open |
| Subject Keyword | Macromolecular Substances Chemistry Microscopy Fluorescent Dyes Likelihood Functions Markov Chains Statistics & Numerical Data Microscopy, Fluorescence Models, Chemical Molecular Imaging Multiprotein Complexes Photochemical Processes Stochastic Processes Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov't Research Support, U.S. Gov't, Non-P.H.S. Multidisciplinary |
| Content Type | Text |
| Resource Type | Article |
| Subject | Multidisciplinary |
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