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Accuracy of the detection of binding events using 3D single particle tracking

Overview of attention for article published in BMC Biophysics, March 2017
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Title
Accuracy of the detection of binding events using 3D single particle tracking
Published in
BMC Biophysics, March 2017
DOI 10.1186/s13628-017-0035-8
Pubmed ID
Authors

Sara Carozza, Jamie Culkin, John van Noort

Abstract

Nanoparticles can be used as markers to track the position of biomolecules, such as single proteins, inside living cells. The activity of a protein can sometimes be inferred from changes in the mobility of the attached particle. Mean Square Displacement analysis is the most common method to obtain mobility information from trajectories of tracked particles, such as the diffusion coefficient D. However, the precision of D sets a limit to discriminate changes in mobility caused by biological events from changes that reflect the stochasticity inherent to diffusion. This issue is of particular importance in an experiment aiming to quantify dynamic processes. Here, we present simulations and 3D tracking experiments with Gold Nanorods freely diffusing in glycerol solution to establish the best analysis parameters to extract the diffusion coefficient. We applied this knowledge to the detection of a temporary change in diffusion, as it can occur due to the transient binding of a particle to an immobile structure within the cell, and tested its dependence on the magnitude of the change in diffusion and duration of this event. The simulations show that the spatial accuracy of particle tracking generally does not limit the detection of short binding events. Careful analysis of the magnitude of the change in diffusion and the number of frames per binding event is required for accurate quantification of such events.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 13 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 13 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 3 23%
Researcher 3 23%
Student > Ph. D. Student 3 23%
Unspecified 1 8%
Student > Doctoral Student 1 8%
Other 2 15%
Readers by discipline Count As %
Physics and Astronomy 6 46%
Engineering 2 15%
Biochemistry, Genetics and Molecular Biology 1 8%
Chemistry 1 8%
Unspecified 1 8%
Other 0 0%
Unknown 2 15%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 23 March 2017.
All research outputs
#21,264,673
of 23,881,329 outputs
Outputs from BMC Biophysics
#52
of 57 outputs
Outputs of similar age
#273,287
of 311,144 outputs
Outputs of similar age from BMC Biophysics
#1
of 1 outputs
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So far Altmetric has tracked 57 research outputs from this source. They receive a mean Attention Score of 4.0. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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