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Extracting predictors for lung adenocarcinoma based on Granger causality test and stepwise character selection

Overview of attention for article published in BMC Bioinformatics, May 2019
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1 X user

Citations

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6 Mendeley
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Title
Extracting predictors for lung adenocarcinoma based on Granger causality test and stepwise character selection
Published in
BMC Bioinformatics, May 2019
DOI 10.1186/s12859-019-2739-z
Pubmed ID
Authors

Xuemeng Fan, Yaolai Wang, Xu-Qing Tang

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user 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 %
Unspecified 1 17%
Researcher 1 17%
Student > Postgraduate 1 17%
Unknown 3 50%
Readers by discipline Count As %
Unspecified 1 17%
Chemistry 1 17%
Medicine and Dentistry 1 17%
Engineering 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 30 December 2021.
All research outputs
#20,255,902
of 22,785,242 outputs
Outputs from BMC Bioinformatics
#6,851
of 7,279 outputs
Outputs of similar age
#298,538
of 349,434 outputs
Outputs of similar age from BMC Bioinformatics
#179
of 189 outputs
Altmetric has tracked 22,785,242 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,279 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 1st percentile – i.e., 1% 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 349,434 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 189 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.