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Novel domain expansion methods to improve the computational efficiency of the Chemical Master Equation solution for large biological networks

Overview of attention for article published in BMC Bioinformatics, November 2020
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (61st percentile)
  • Above-average Attention Score compared to outputs of the same age and source (57th percentile)

Mentioned by

twitter
3 tweeters
wikipedia
1 Wikipedia page

Citations

dimensions_citation
1 Dimensions

Readers on

mendeley
14 Mendeley
Title
Novel domain expansion methods to improve the computational efficiency of the Chemical Master Equation solution for large biological networks
Published in
BMC Bioinformatics, November 2020
DOI 10.1186/s12859-020-03668-2
Pubmed ID
Authors

Rahul Kosarwal, Don Kulasiri, Sandhya Samarasinghe

Twitter Demographics

The data shown below were collected from the profiles of 3 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 14 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 14 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 3 21%
Student > Ph. D. Student 2 14%
Student > Master 2 14%
Student > Bachelor 1 7%
Unspecified 1 7%
Other 1 7%
Unknown 4 29%
Readers by discipline Count As %
Engineering 2 14%
Physics and Astronomy 2 14%
Business, Management and Accounting 1 7%
Nursing and Health Professions 1 7%
Biochemistry, Genetics and Molecular Biology 1 7%
Other 4 29%
Unknown 3 21%

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 21 November 2021.
All research outputs
#6,697,896
of 22,520,629 outputs
Outputs from BMC Bioinformatics
#2,580
of 7,209 outputs
Outputs of similar age
#153,121
of 399,902 outputs
Outputs of similar age from BMC Bioinformatics
#207
of 484 outputs
Altmetric has tracked 22,520,629 research outputs across all sources so far. This one has received more attention than most of these and is in the 69th percentile.
So far Altmetric has tracked 7,209 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one has gotten more attention than average, scoring higher than 63% 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 399,902 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 61% of its contemporaries.
We're also able to compare this research output to 484 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 57% of its contemporaries.