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Editorial: Decoding novel therapeutic targets, biomarkers, and drug development strategies against neurodegenerative disorders—A multi-omics approach

Overview of attention for article published in Frontiers in Computational Neuroscience, June 2023
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (77th percentile)
  • High Attention Score compared to outputs of the same age and source (99th percentile)

Mentioned by

news
1 news outlet

Citations

dimensions_citation
1 Dimensions

Readers on

mendeley
3 Mendeley
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Title
Editorial: Decoding novel therapeutic targets, biomarkers, and drug development strategies against neurodegenerative disorders—A multi-omics approach
Published in
Frontiers in Computational Neuroscience, June 2023
DOI 10.3389/fncom.2023.1227850
Pubmed ID
Authors

E. Srinivasan, Siranjeevi Nagaraj, Sakthi Rajendran, R. Rajasekaran

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 3 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 3 100%

Demographic breakdown

Readers by professional status Count As %
Professor 1 33%
Student > Bachelor 1 33%
Unknown 1 33%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 1 33%
Psychology 1 33%
Unknown 1 33%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 7. 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 2023.
All research outputs
#4,508,773
of 24,076,951 outputs
Outputs from Frontiers in Computational Neuroscience
#203
of 1,397 outputs
Outputs of similar age
#53,502
of 253,650 outputs
Outputs of similar age from Frontiers in Computational Neuroscience
#1
of 12 outputs
Altmetric has tracked 24,076,951 research outputs across all sources so far. Compared to these this one has done well and is in the 80th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,397 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.0. This one has done well, scoring higher than 85% 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 253,650 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 77% of its contemporaries.
We're also able to compare this research output to 12 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 99% of its contemporaries.