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Correction: Using empirical biological knowledge to infer regulatory networks from multi-omics data

Overview of attention for article published in BMC Bioinformatics, September 2022
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Title
Correction: Using empirical biological knowledge to infer regulatory networks from multi-omics data
Published in
BMC Bioinformatics, September 2022
DOI 10.1186/s12859-022-04931-4
Pubmed ID
Authors

Anna Pačínková, Vlad Popovici

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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 17 September 2022.
All research outputs
#19,902,159
of 24,457,696 outputs
Outputs from BMC Bioinformatics
#6,552
of 7,535 outputs
Outputs of similar age
#309,409
of 422,052 outputs
Outputs of similar age from BMC Bioinformatics
#138
of 139 outputs
Altmetric has tracked 24,457,696 research outputs across all sources so far. This one is in the 10th percentile – i.e., 10% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,535 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one is in the 5th percentile – i.e., 5% 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 422,052 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 15th percentile – i.e., 15% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 139 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.