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Mesoscale modeling: solving complex flows in biology and biotechnology

Overview of attention for article published in Trends in Biotechnology, June 2013
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Citations

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131 Mendeley
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Title
Mesoscale modeling: solving complex flows in biology and biotechnology
Published in
Trends in Biotechnology, June 2013
DOI 10.1016/j.tibtech.2013.05.001
Pubmed ID
Authors

Zachary Grant Mills, Wenbin Mao, Alexander Alexeev

Abstract

Fluids are involved in practically all physiological activities of living organisms. However, biological and biorelated flows are hard to analyze due to the inherent combination of interdependent effects and processes that occur on a multitude of spatial and temporal scales. Recent advances in mesoscale simulations enable researchers to tackle problems that are central for the understanding of such flows. Furthermore, computational modeling effectively facilitates the development of novel therapeutic approaches. Among other methods, dissipative particle dynamics and the lattice Boltzmann method have become increasingly popular during recent years due to their ability to solve a large variety of problems. In this review, we discuss recent applications of these mesoscale methods to several fluid-related problems in medicine, bioengineering, and biotechnology.

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 131 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 5 4%
United Kingdom 2 2%
Netherlands 1 <1%
Australia 1 <1%
Switzerland 1 <1%
Israel 1 <1%
Germany 1 <1%
Romania 1 <1%
Brazil 1 <1%
Other 0 0%
Unknown 117 89%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 35 27%
Researcher 28 21%
Student > Master 13 10%
Professor > Associate Professor 8 6%
Professor 7 5%
Other 25 19%
Unknown 15 11%
Readers by discipline Count As %
Engineering 41 31%
Agricultural and Biological Sciences 16 12%
Chemistry 11 8%
Physics and Astronomy 9 7%
Biochemistry, Genetics and Molecular Biology 8 6%
Other 23 18%
Unknown 23 18%
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 20 November 2017.
All research outputs
#16,046,765
of 25,371,288 outputs
Outputs from Trends in Biotechnology
#2,535
of 2,856 outputs
Outputs of similar age
#122,109
of 209,898 outputs
Outputs of similar age from Trends in Biotechnology
#17
of 24 outputs
Altmetric has tracked 25,371,288 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 2,856 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.5. This one is in the 9th percentile – i.e., 9% 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 209,898 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 39th percentile – i.e., 39% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 24 others from the same source and published within six weeks on either side of this one. This one is in the 29th percentile – i.e., 29% of its contemporaries scored the same or lower than it.