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Integrative eQTL-weighted hierarchical Cox models for SNP-set based time-to-event association studies

Overview of attention for article published in Journal of Translational Medicine, October 2021
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Mentioned by

twitter
1 tweeter

Citations

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1 Dimensions

Readers on

mendeley
6 Mendeley
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Title
Integrative eQTL-weighted hierarchical Cox models for SNP-set based time-to-event association studies
Published in
Journal of Translational Medicine, October 2021
DOI 10.1186/s12967-021-03090-z
Pubmed ID
Authors

Haojie Lu, Yongyue Wei, Zhou Jiang, Jinhui Zhang, Ting Wang, Shuiping Huang, Ping Zeng

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter 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 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 2 33%
Lecturer 1 17%
Student > Doctoral Student 1 17%
Unknown 2 33%
Readers by discipline Count As %
Unspecified 2 33%
Biochemistry, Genetics and Molecular Biology 1 17%
Economics, Econometrics and Finance 1 17%
Unknown 2 33%

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 11 October 2021.
All research outputs
#19,790,703
of 22,223,421 outputs
Outputs from Journal of Translational Medicine
#3,203
of 3,859 outputs
Outputs of similar age
#291,285
of 351,911 outputs
Outputs of similar age from Journal of Translational Medicine
#1
of 1 outputs
Altmetric has tracked 22,223,421 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 3,859 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.3. 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 351,911 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 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