Characterizing Single-Molecule FRET Dynamics with Probability Distribution Analysis

ChemPhysChem ◽  
2010 ◽  
Vol 11 (10) ◽  
pp. 2209-2219 ◽  
Author(s):  
Yusdi Santoso ◽  
Joseph P. Torella ◽  
Achillefs N. Kapanidis
Keyword(s):  
Probability Distribution ◽  
Single Molecule ◽  
Distribution Analysis ◽  
Single Molecule Fret

scholarly journals Camera-based single-molecule FRET detection with improved time resolution

2015 ◽  
Vol 17 (41) ◽  
pp. 27862-27872 ◽  
Author(s):  
Shazia Farooq ◽  
Johannes Hohlbein
Keyword(s):  
Probability Distribution ◽  
Single Molecule ◽  
Time Resolution ◽  
Laser Excitation ◽  
Single Molecule Detection ◽  
Distribution Analysis ◽  
Single Molecule Fret ◽  
Alternating Laser Excitation

Here the authors report on significant improvements in time-resolution and throughput in camera-based single-molecule detection by combining stroboscopic alternating-laser excitation with dynamic probability distribution analysis.

scholarly journals Disentangling Subpopulations in Single-Molecule FRET and ALEX Experiments with Photon Distribution Analysis

2012 ◽  
Vol 102 (5) ◽  
pp. 1163-1173 ◽  
Author(s):  
Toma E. Tomov ◽  
Roman Tsukanov ◽  
Rula Masoud ◽  
Miran Liber ◽  
Noa Plavner ◽  
...  
Keyword(s):  
Single Molecule ◽  
Distribution Analysis ◽  
Photon Distribution ◽  
Single Molecule Fret

Distribution Analysis for Single Molecule FRET Measurement

2008 ◽  
Vol 112 (24) ◽  
pp. 7308-7314 ◽  
Author(s):  
Kenji Okamoto ◽  
Masahide Terazima
Keyword(s):  
Single Molecule ◽  
Distribution Analysis ◽  
Single Molecule Fret

scholarly journals Blinking statistics and molecular counting in direct stochastic reconstruction microscopy (dSTORM)

2021 ◽  
Author(s):  
Lekha Patel ◽  
David Williamson ◽  
Dylan M Owen ◽  
Edward A K Cohen
Keyword(s):  
Probability Distribution ◽  
Single Molecule ◽  
Immunological Synapse ◽  
Training Data ◽  
Supplementary Information ◽  
Cellular Structures ◽  
Exact Probability ◽  
Stochastic Optical Reconstruction Microscopy ◽  
Exact Probability Distribution ◽  
Optical Reconstruction

Abstract Motivation Many recent advancements in single-molecule localization microscopy exploit the stochastic photoswitching of fluorophores to reveal complex cellular structures beyond the classical diffraction limit. However, this same stochasticity makes counting the number of molecules to high precision extremely challenging, preventing key insight into the cellular structures and processes under observation. Results Modelling the photoswitching behaviour of a fluorophore as an unobserved continuous time Markov process transitioning between a single fluorescent and multiple dark states, and fully mitigating for missed blinks and false positives, we present a method for computing the exact probability distribution for the number of observed localizations from a single photoswitching fluorophore. This is then extended to provide the probability distribution for the number of localizations in a direct stochastic optical reconstruction microscopy experiment involving an arbitrary number of molecules. We demonstrate that when training data are available to estimate photoswitching rates, the unknown number of molecules can be accurately recovered from the posterior mode of the number of molecules given the number of localizations. Finally, we demonstrate the method on experimental data by quantifying the number of adapter protein linker for activation of T cells on the cell surface of the T-cell immunological synapse. Availability and implementation Software and data available at https://github.com/lp1611/mol_count_dstorm. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals Encoding Multiple Virtual Signals in DNA Barcodes with Single-Molecule FRET

Nano Letters ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1694-1701 ◽  
Author(s):  
Sung Hyun Kim ◽  
Hyunwoo Kim ◽  
Hawoong Jeong ◽  
Tae-Young Yoon
Keyword(s):  
Single Molecule ◽  
Dna Barcodes ◽  
Single Molecule Fret
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