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A new Bayesian piecewise linear regression model for dynamic network reconstruction

Overview of attention for article published in BMC Bioinformatics, April 2021
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Mentioned by

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2 X users

Citations

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7 Dimensions

Readers on

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6 Mendeley
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Title
A new Bayesian piecewise linear regression model for dynamic network reconstruction
Published in
BMC Bioinformatics, April 2021
DOI 10.1186/s12859-021-03998-9
Pubmed ID
Authors

Mahdi Shafiee Kamalabad, Marco Grzegorczyk

X Demographics

X Demographics

The data shown below were collected from the profiles of 2 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 %
Researcher 3 50%
Student > Bachelor 1 17%
Student > Doctoral Student 1 17%
Unknown 1 17%
Readers by discipline Count As %
Computer Science 3 50%
Economics, Econometrics and Finance 1 17%
Unknown 2 33%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 28 April 2021.
All research outputs
#18,143,395
of 23,308,124 outputs
Outputs from BMC Bioinformatics
#6,043
of 7,380 outputs
Outputs of similar age
#303,049
of 436,647 outputs
Outputs of similar age from BMC Bioinformatics
#186
of 193 outputs
Altmetric has tracked 23,308,124 research outputs across all sources so far. This one is in the 19th percentile – i.e., 19% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,380 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one is in the 13th percentile – i.e., 13% 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 436,647 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 26th percentile – i.e., 26% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 193 others from the same source and published within six weeks on either side of this one. This one is in the 2nd percentile – i.e., 2% of its contemporaries scored the same or lower than it.