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Transport Effects on Multiple-Component Reactions in Optical Biosensors

Overview of attention for article published in Bulletin of Mathematical Biology, August 2017
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5 Mendeley
Title
Transport Effects on Multiple-Component Reactions in Optical Biosensors
Published in
Bulletin of Mathematical Biology, August 2017
DOI 10.1007/s11538-017-0327-9
Pubmed ID
Authors

Ryan M. Evans, David A. Edwards

Abstract

Optical biosensors are often used to measure kinetic rate constants associated with chemical reactions. Such instruments operate in the surface-volume configuration, in which ligand molecules are convected through a fluid-filled volume over a surface to which receptors are confined. Currently, scientists are using optical biosensors to measure the kinetic rate constants associated with DNA translesion synthesis-a process critical to DNA damage repair. Biosensor experiments to study this process involve multiple interacting components on the sensor surface. This multiple-component biosensor experiment is modeled with a set of nonlinear integrodifferential equations (IDEs). It is shown that in physically relevant asymptotic limits these equations reduce to a much simpler set of ordinary differential equations (ODEs). To verify the validity of our ODE approximation, a numerical method for the IDE system is developed and studied. Results from the ODE model agree with simulations of the IDE model, rendering our ODE model useful for parameter estimation.

X Demographics

X Demographics

The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 5 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 5 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 3 60%
Student > Bachelor 1 20%
Unknown 1 20%
Readers by discipline Count As %
Engineering 2 40%
Chemistry 1 20%
Agricultural and Biological Sciences 1 20%
Unknown 1 20%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 13 October 2017.
All research outputs
#15,317,599
of 24,286,850 outputs
Outputs from Bulletin of Mathematical Biology
#664
of 1,158 outputs
Outputs of similar age
#181,292
of 320,812 outputs
Outputs of similar age from Bulletin of Mathematical Biology
#10
of 23 outputs
Altmetric has tracked 24,286,850 research outputs across all sources so far. This one is in the 34th percentile – i.e., 34% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,158 research outputs from this source. They receive a mean Attention Score of 4.9. This one is in the 38th percentile – i.e., 38% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 320,812 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 40th percentile – i.e., 40% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 23 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 60% of its contemporaries.