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Multiscale modeling and uncertainty quantification in nanoparticle-mediated drug/gene delivery

Overview of attention for article published in Computational Mechanics, November 2013
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1 X user

Citations

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Readers on

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60 Mendeley
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1 CiteULike
Title
Multiscale modeling and uncertainty quantification in nanoparticle-mediated drug/gene delivery
Published in
Computational Mechanics, November 2013
DOI 10.1007/s00466-013-0953-5
Authors

Ying Li, Wylie Stroberg, Tae-Rin Lee, Han Sung Kim, Han Man, Dean Ho, Paolo Decuzzi, Wing Kam Liu

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user 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 60 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Spain 1 2%
United States 1 2%
China 1 2%
Italy 1 2%
Unknown 56 93%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 20 33%
Researcher 15 25%
Student > Master 6 10%
Professor 3 5%
Student > Doctoral Student 3 5%
Other 7 12%
Unknown 6 10%
Readers by discipline Count As %
Engineering 16 27%
Chemistry 7 12%
Materials Science 6 10%
Agricultural and Biological Sciences 3 5%
Chemical Engineering 3 5%
Other 10 17%
Unknown 15 25%
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 06 December 2013.
All research outputs
#21,285,712
of 26,017,215 outputs
Outputs from Computational Mechanics
#222
of 304 outputs
Outputs of similar age
#250,191
of 326,976 outputs
Outputs of similar age from Computational Mechanics
#6
of 7 outputs
Altmetric has tracked 26,017,215 research outputs across all sources so far. This one is in the 10th percentile – i.e., 10% of other outputs scored the same or lower than it.
So far Altmetric has tracked 304 research outputs from this source. They receive a mean Attention Score of 3.4. This one is in the 19th percentile – i.e., 19% 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 326,976 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 11th percentile – i.e., 11% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 7 others from the same source and published within six weeks on either side of this one.