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A new massively parallel nanoball sequencing platform for whole exome research

Overview of attention for article published in BMC Bioinformatics, March 2019
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (89th percentile)
  • High Attention Score compared to outputs of the same age and source (95th percentile)

Mentioned by

blogs
1 blog
twitter
21 X users

Citations

dimensions_citation
52 Dimensions

Readers on

mendeley
62 Mendeley
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Title
A new massively parallel nanoball sequencing platform for whole exome research
Published in
BMC Bioinformatics, March 2019
DOI 10.1186/s12859-019-2751-3
Pubmed ID
Authors

Yu Xu, Zhe Lin, Chong Tang, Yujing Tang, Yue Cai, Hongbin Zhong, Xuebin Wang, Wenwei Zhang, Chongjun Xu, Jingjing Wang, Jian Wang, Huanming Yang, Linfeng Yang, Qiang Gao

X Demographics

X Demographics

The data shown below were collected from the profiles of 21 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 62 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 62 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 10 16%
Student > Master 8 13%
Researcher 8 13%
Student > Doctoral Student 4 6%
Student > Bachelor 3 5%
Other 8 13%
Unknown 21 34%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 18 29%
Agricultural and Biological Sciences 10 16%
Engineering 2 3%
Computer Science 2 3%
Pharmacology, Toxicology and Pharmaceutical Science 1 2%
Other 6 10%
Unknown 23 37%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 23. 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 06 August 2021.
All research outputs
#1,626,077
of 24,998,746 outputs
Outputs from BMC Bioinformatics
#275
of 7,630 outputs
Outputs of similar age
#36,695
of 357,590 outputs
Outputs of similar age from BMC Bioinformatics
#9
of 164 outputs
Altmetric has tracked 24,998,746 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 93rd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,630 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one has done particularly well, scoring higher than 96% 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 357,590 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 89% of its contemporaries.
We're also able to compare this research output to 164 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 95% of its contemporaries.