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Macromolecular Crowding Meets Tissue Engineering by Self‐Assembly: A Paradigm Shift in Regenerative Medicine

Overview of attention for article published in Advanced Materials, February 2014
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (85th percentile)
  • Good Attention Score compared to outputs of the same age and source (71st percentile)

Mentioned by

patent
2 patents
wikipedia
1 Wikipedia page

Citations

dimensions_citation
148 Dimensions

Readers on

mendeley
171 Mendeley
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Title
Macromolecular Crowding Meets Tissue Engineering by Self‐Assembly: A Paradigm Shift in Regenerative Medicine
Published in
Advanced Materials, February 2014
DOI 10.1002/adma.201304428
Pubmed ID
Authors

Abhigyan Satyam, Pramod Kumar, Xingliang Fan, Alexander Gorelov, Yury Rochev, Lokesh Joshi, Héctor Peinado, David Lyden, Benjamin Thomas, Brian Rodriguez, Michael Raghunath, Abhay Pandit, Dimitrios Zeugolis

Abstract

MMC, the addition of inert polydispersed macromolecules in the culture media, effectively emulates the dense in vivo extracellular space, resulting in amplified deposition of ECM in vitro and subsequent production of cohesive, ECM-rich living substitutes.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 171 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Ireland 1 <1%
Italy 1 <1%
Sweden 1 <1%
India 1 <1%
Russia 1 <1%
Spain 1 <1%
Unknown 165 96%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 35 20%
Researcher 23 13%
Student > Master 23 13%
Student > Bachelor 18 11%
Student > Doctoral Student 14 8%
Other 18 11%
Unknown 40 23%
Readers by discipline Count As %
Agricultural and Biological Sciences 35 20%
Biochemistry, Genetics and Molecular Biology 22 13%
Engineering 20 12%
Medicine and Dentistry 15 9%
Chemistry 11 6%
Other 21 12%
Unknown 47 27%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 9. 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 14 July 2020.
All research outputs
#3,655,648
of 24,698,625 outputs
Outputs from Advanced Materials
#3,449
of 16,673 outputs
Outputs of similar age
#42,897
of 318,578 outputs
Outputs of similar age from Advanced Materials
#46
of 174 outputs
Altmetric has tracked 24,698,625 research outputs across all sources so far. Compared to these this one has done well and is in the 84th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 16,673 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.1. This one has done well, scoring higher than 76% of its peers.
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 318,578 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 85% of its contemporaries.
We're also able to compare this research output to 174 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 71% of its contemporaries.