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X Demographics
Mendeley readers
Attention Score in Context
| Title |
TIGER: tiled iterative genome assembler
|
|---|---|
| Published in |
BMC Bioinformatics, December 2012
|
| DOI | 10.1186/1471-2105-13-s19-s18 |
| Pubmed ID | |
| Authors |
Xiao-Long Wu, Yun Heo, Izzat El Hajj, Wen-Mei Hwu, Deming Chen, Jian Ma |
| Abstract |
With the cost reduction of the next-generation sequencing (NGS) technologies, genomics has provided us with an unprecedented opportunity to understand fundamental questions in biology and elucidate human diseases. De novo genome assembly is one of the most important steps to reconstruct the sequenced genome. However, most de novo assemblers require enormous amount of computational resource, which is not accessible for most research groups and medical personnel. |
X Demographics
The data shown below were collected from the profiles of 14 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Germany | 3 | 21% |
| United States | 3 | 21% |
| United Kingdom | 2 | 14% |
| Norway | 1 | 7% |
| Sweden | 1 | 7% |
| Australia | 1 | 7% |
| Canada | 1 | 7% |
| Unknown | 2 | 14% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 10 | 71% |
| Members of the public | 3 | 21% |
| Practitioners (doctors, other healthcare professionals) | 1 | 7% |
Mendeley readers
The data shown below were compiled from readership statistics for 59 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 6 | 10% |
| Brazil | 1 | 2% |
| Sweden | 1 | 2% |
| Netherlands | 1 | 2% |
| Argentina | 1 | 2% |
| United Kingdom | 1 | 2% |
| Japan | 1 | 2% |
| Spain | 1 | 2% |
| Unknown | 46 | 78% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 22 | 37% |
| Student > Ph. D. Student | 15 | 25% |
| Student > Master | 8 | 14% |
| Student > Bachelor | 5 | 8% |
| Professor > Associate Professor | 3 | 5% |
| Other | 3 | 5% |
| Unknown | 3 | 5% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 29 | 49% |
| Computer Science | 9 | 15% |
| Biochemistry, Genetics and Molecular Biology | 8 | 14% |
| Environmental Science | 3 | 5% |
| Engineering | 3 | 5% |
| Other | 2 | 3% |
| Unknown | 5 | 8% |
Attention Score in Context
This research output has an Altmetric Attention Score of 7. 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 15 January 2013.
All research outputs
#4,705,833
of 23,891,012 outputs
Outputs from BMC Bioinformatics
#1,725
of 7,455 outputs
Outputs of similar age
#48,511
of 285,652 outputs
Outputs of similar age from BMC Bioinformatics
#28
of 135 outputs
Altmetric has tracked 23,891,012 research outputs across all sources so far. Compared to these this one has done well and is in the 80th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,455 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 well, scoring higher than 76% 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 285,652 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 82% of its contemporaries.
We're also able to compare this research output to 135 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 80% of its contemporaries.