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 |
Efficient alignment of pyrosequencing reads for re-sequencing applications
|
|---|---|
| Published in |
BMC Bioinformatics, May 2011
|
| DOI | 10.1186/1471-2105-12-163 |
| Pubmed ID | |
| Authors |
Francisco Fernandes, Paulo GS da Fonseca, Luis MS Russo, Arlindo L Oliveira, Ana T Freitas |
| Abstract |
Over the past few years, new massively parallel DNA sequencing technologies have emerged. These platforms generate massive amounts of data per run, greatly reducing the cost of DNA sequencing. However, these techniques also raise important computational difficulties mostly due to the huge volume of data produced, but also because of some of their specific characteristics such as read length and sequencing errors. Among the most critical problems is that of efficiently and accurately mapping reads to a reference genome in the context of re-sequencing projects. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 52 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Brazil | 3 | 6% |
| Germany | 1 | 2% |
| France | 1 | 2% |
| Sweden | 1 | 2% |
| United Kingdom | 1 | 2% |
| Spain | 1 | 2% |
| Unknown | 44 | 85% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 15 | 29% |
| Professor > Associate Professor | 11 | 21% |
| Student > Ph. D. Student | 10 | 19% |
| Professor | 5 | 10% |
| Other | 2 | 4% |
| Other | 7 | 13% |
| Unknown | 2 | 4% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 30 | 58% |
| Computer Science | 6 | 12% |
| Biochemistry, Genetics and Molecular Biology | 3 | 6% |
| Environmental Science | 2 | 4% |
| Engineering | 2 | 4% |
| Other | 6 | 12% |
| Unknown | 3 | 6% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. 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 24 April 2012.
All research outputs
#18,305,773
of 22,664,644 outputs
Outputs from BMC Bioinformatics
#6,283
of 7,247 outputs
Outputs of similar age
#95,282
of 110,558 outputs
Outputs of similar age from BMC Bioinformatics
#73
of 85 outputs
Altmetric has tracked 22,664,644 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
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 is in the 5th percentile – i.e., 5% of its peers scored the same or lower than it.
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 110,558 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 6th percentile – i.e., 6% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 85 others from the same source and published within six weeks on either side of this one. This one is in the 4th percentile – i.e., 4% of its contemporaries scored the same or lower than it.