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MEMMAL: A tool for expanding large-scale mechanistic models with machine learned associations and big datasets

Overview of attention for article published in Frontiers in Systems Biology, March 2023
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (70th percentile)

Mentioned by

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8 X users

Citations

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2 Dimensions

Readers on

mendeley
6 Mendeley
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Title
MEMMAL: A tool for expanding large-scale mechanistic models with machine learned associations and big datasets
Published in
Frontiers in Systems Biology, March 2023
DOI 10.3389/fsysb.2023.1099413
Pubmed ID
Authors

Cemal Erdem, Marc R. Birtwistle

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.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 6 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 6 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 3 50%
Student > Doctoral Student 2 33%
Researcher 1 17%
Readers by discipline Count As %
Chemical Engineering 2 33%
Computer Science 2 33%
Biochemistry, Genetics and Molecular Biology 1 17%
Agricultural and Biological Sciences 1 17%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 5. 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 10 July 2023.
All research outputs
#7,209,485
of 25,992,468 outputs
Outputs from Frontiers in Systems Biology
#1
of 1 outputs
Outputs of similar age
#125,399
of 428,972 outputs
Outputs of similar age from Frontiers in Systems Biology
#1
of 1 outputs
Altmetric has tracked 25,992,468 research outputs across all sources so far. This one has received more attention than most of these and is in the 72nd percentile.
So far Altmetric has tracked 1 research outputs from this source. They receive a mean Attention Score of 4.6. This one scored the same or higher as 0 of them.
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 428,972 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 70% of its contemporaries.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them