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Mendeley readers
Attention Score in Context
Title |
ngs.plot: Quick mining and visualization of next-generation sequencing data by integrating genomic databases
|
---|---|
Published in |
BMC Genomics, April 2014
|
DOI | 10.1186/1471-2164-15-284 |
Pubmed ID | |
Authors |
Li Shen, Ningyi Shao, Xiaochuan Liu, Eric Nestler |
Abstract |
Understanding the relationship between the millions of functional DNA elements and their protein regulators, and how they work in conjunction to manifest diverse phenotypes, is key to advancing our understanding of the mammalian genome. Next-generation sequencing technology is now used widely to probe these protein-DNA interactions and to profile gene expression at a genome-wide scale. As the cost of DNA sequencing continues to fall, the interpretation of the ever increasing amount of data generated represents a considerable challenge. |
X Demographics
The data shown below were collected from the profiles of 15 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 | 5 | 33% |
France | 2 | 13% |
United Kingdom | 1 | 7% |
Austria | 1 | 7% |
Canada | 1 | 7% |
Montenegro | 1 | 7% |
Unknown | 4 | 27% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Scientists | 9 | 60% |
Members of the public | 5 | 33% |
Practitioners (doctors, other healthcare professionals) | 1 | 7% |
Mendeley readers
The data shown below were compiled from readership statistics for 472 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 8 | 2% |
United Kingdom | 4 | <1% |
Germany | 2 | <1% |
China | 2 | <1% |
Spain | 2 | <1% |
Norway | 1 | <1% |
Brazil | 1 | <1% |
Portugal | 1 | <1% |
Belgium | 1 | <1% |
Other | 6 | 1% |
Unknown | 444 | 94% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 123 | 26% |
Student > Ph. D. Student | 98 | 21% |
Student > Master | 44 | 9% |
Student > Bachelor | 31 | 7% |
Student > Doctoral Student | 25 | 5% |
Other | 73 | 15% |
Unknown | 78 | 17% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 178 | 38% |
Biochemistry, Genetics and Molecular Biology | 127 | 27% |
Computer Science | 31 | 7% |
Medicine and Dentistry | 14 | 3% |
Neuroscience | 9 | 2% |
Other | 27 | 6% |
Unknown | 86 | 18% |
Attention Score in Context
This research output has an Altmetric Attention Score of 19. 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 22 November 2023.
All research outputs
#1,907,683
of 25,371,288 outputs
Outputs from BMC Genomics
#415
of 11,244 outputs
Outputs of similar age
#18,846
of 239,868 outputs
Outputs of similar age from BMC Genomics
#9
of 221 outputs
Altmetric has tracked 25,371,288 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 92nd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 11,244 research outputs from this source. They receive a mean Attention Score of 4.8. 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 239,868 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 92% of its contemporaries.
We're also able to compare this research output to 221 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.