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Decoding the Role of Epigenetics in Breast Cancer Using Formal Modeling and Machine-Learning Methods

Overview of attention for article published in Frontiers in Molecular Biosciences, July 2022
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (62nd percentile)
  • High Attention Score compared to outputs of the same age and source (89th percentile)

Mentioned by

twitter
8 X users

Readers on

mendeley
5 Mendeley
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Title
Decoding the Role of Epigenetics in Breast Cancer Using Formal Modeling and Machine-Learning Methods
Published in
Frontiers in Molecular Biosciences, July 2022
DOI 10.3389/fmolb.2022.882738
Pubmed ID
Authors

Ayesha Asim, Yusra Sajid Kiani, Muhammad Tariq Saeed, Ishrat Jabeen

X Demographics

X Demographics

The data shown below were collected from the profiles of 8 X users who shared this research output. Click here to find out more about how the information was compiled.
As of 1 July 2024, you may notice a temporary increase in the numbers of X profiles with Unknown location. Click here to learn more.
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 %
Unspecified 1 20%
Lecturer 1 20%
Other 1 20%
Student > Master 1 20%
Unknown 1 20%
Readers by discipline Count As %
Unspecified 1 20%
Environmental Science 1 20%
Business, Management and Accounting 1 20%
Medicine and Dentistry 1 20%
Unknown 1 20%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 31 July 2022.
All research outputs
#8,043,085
of 24,176,645 outputs
Outputs from Frontiers in Molecular Biosciences
#842
of 4,315 outputs
Outputs of similar age
#149,658
of 423,263 outputs
Outputs of similar age from Frontiers in Molecular Biosciences
#44
of 391 outputs
Altmetric has tracked 24,176,645 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 4,315 research outputs from this source. They receive a mean Attention Score of 3.3. This one has done well, scoring higher than 80% 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 423,263 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 62% of its contemporaries.
We're also able to compare this research output to 391 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 89% of its contemporaries.