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X Demographics
Mendeley readers
Attention Score in Context
| Title |
A new strategy for better genome assembly from very short reads
|
|---|---|
| Published in |
BMC Bioinformatics, December 2011
|
| DOI | 10.1186/1471-2105-12-493 |
| Pubmed ID | |
| Authors |
Yan Ji, Yixiang Shi, Guohui Ding, Yixue Li |
| Abstract |
With the rapid development of the next generation sequencing (NGS) technology, large quantities of genome sequencing data have been generated. Because of repetitive regions of genomes and some other factors, assembly of very short reads is still a challenging issue. |
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 Kingdom | 3 | 20% |
| Colombia | 2 | 13% |
| Australia | 1 | 7% |
| Germany | 1 | 7% |
| Sweden | 1 | 7% |
| France | 1 | 7% |
| Japan | 1 | 7% |
| Cameroon | 1 | 7% |
| Unknown | 4 | 27% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 10 | 67% |
| Scientists | 5 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 127 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Brazil | 6 | 5% |
| United States | 5 | 4% |
| Sweden | 3 | 2% |
| United Kingdom | 2 | 2% |
| Argentina | 2 | 2% |
| Norway | 1 | <1% |
| India | 1 | <1% |
| Australia | 1 | <1% |
| Mexico | 1 | <1% |
| Other | 6 | 5% |
| Unknown | 99 | 78% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 42 | 33% |
| Student > Ph. D. Student | 26 | 20% |
| Student > Master | 13 | 10% |
| Student > Bachelor | 9 | 7% |
| Professor > Associate Professor | 9 | 7% |
| Other | 23 | 18% |
| Unknown | 5 | 4% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 83 | 65% |
| Computer Science | 13 | 10% |
| Biochemistry, Genetics and Molecular Biology | 11 | 9% |
| Engineering | 5 | 4% |
| Mathematics | 2 | 2% |
| Other | 4 | 3% |
| Unknown | 9 | 7% |
Attention Score in Context
This research output has an Altmetric Attention Score of 9. 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 18 May 2012.
All research outputs
#3,602,311
of 23,023,224 outputs
Outputs from BMC Bioinformatics
#1,295
of 7,316 outputs
Outputs of similar age
#30,149
of 245,052 outputs
Outputs of similar age from BMC Bioinformatics
#18
of 96 outputs
Altmetric has tracked 23,023,224 research outputs across all sources so far. Compared to these this one has done well and is in the 84th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,316 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one has done well, scoring higher than 82% 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 245,052 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 87% of its contemporaries.
We're also able to compare this research output to 96 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 82% of its contemporaries.