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X Demographics
Mendeley readers
Attention Score in Context
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
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.
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 3 | 14% |
United Kingdom | 2 | 10% |
China | 2 | 10% |
Hong Kong | 1 | 5% |
Unknown | 13 | 62% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 15 | 71% |
Scientists | 6 | 29% |
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
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.