You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output.
Click here to find out more.
X Demographics
Mendeley readers
Attention Score in Context
Title |
Exploiting sparseness in de novo genome assembly
|
---|---|
Published in |
BMC Bioinformatics, April 2012
|
DOI | 10.1186/1471-2105-13-s6-s1 |
Pubmed ID | |
Authors |
Chengxi Ye, Zhanshan Sam Ma, Charles H Cannon, Mihai Pop, Douglas W Yu |
Abstract |
The very large memory requirements for the construction of assembly graphs for de novo genome assembly limit current algorithms to super-computing environments. |
X Demographics
The data shown below were collected from the profiles of 11 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
Country | Count | As % |
---|---|---|
Japan | 2 | 18% |
China | 1 | 9% |
Norway | 1 | 9% |
Canada | 1 | 9% |
Australia | 1 | 9% |
United Kingdom | 1 | 9% |
Unknown | 4 | 36% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 8 | 73% |
Scientists | 3 | 27% |
Mendeley readers
The data shown below were compiled from readership statistics for 187 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 9 | 5% |
Germany | 2 | 1% |
Korea, Republic of | 2 | 1% |
Brazil | 2 | 1% |
Italy | 1 | <1% |
Chile | 1 | <1% |
Mexico | 1 | <1% |
Sweden | 1 | <1% |
Japan | 1 | <1% |
Other | 1 | <1% |
Unknown | 166 | 89% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 42 | 22% |
Researcher | 40 | 21% |
Student > Master | 36 | 19% |
Student > Bachelor | 21 | 11% |
Other | 11 | 6% |
Other | 19 | 10% |
Unknown | 18 | 10% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 90 | 48% |
Computer Science | 36 | 19% |
Biochemistry, Genetics and Molecular Biology | 25 | 13% |
Engineering | 3 | 2% |
Business, Management and Accounting | 2 | 1% |
Other | 7 | 4% |
Unknown | 24 | 13% |
Attention Score in Context
This research output has an Altmetric Attention Score of 15. 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 30 June 2016.
All research outputs
#2,048,948
of 22,668,244 outputs
Outputs from BMC Bioinformatics
#536
of 7,247 outputs
Outputs of similar age
#12,934
of 161,921 outputs
Outputs of similar age from BMC Bioinformatics
#11
of 97 outputs
Altmetric has tracked 22,668,244 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 90th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,247 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 particularly well, scoring higher than 92% 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 161,921 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 97 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 88% of its contemporaries.