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X Demographics
Mendeley readers
Attention Score in Context
| Title |
DB2: a probabilistic approach for accurate detection of tandem duplication breakpoints using paired-end reads
|
|---|---|
| Published in |
BMC Genomics, March 2014
|
| DOI | 10.1186/1471-2164-15-175 |
| Pubmed ID | |
| Authors |
Gökhan Yavaş, Mehmet Koyutürk, Meetha P Gould, Sarah McMahon, Thomas LaFramboise |
| Abstract |
With the advent of paired-end high throughput sequencing, it is now possible to identify various types of structural variation on a genome-wide scale. Although many methods have been proposed for structural variation detection, most do not provide precise boundaries for identified variants. In this paper, we propose a new method, Distribution Based detection of Duplication Boundaries (DB2), for accurate detection of tandem duplication breakpoints, an important class of structural variation, with high precision and recall. |
X Demographics
The data shown below were collected from the profiles of 6 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Canada | 1 | 17% |
| United States | 1 | 17% |
| Sweden | 1 | 17% |
| Israel | 1 | 17% |
| Germany | 1 | 17% |
| Unknown | 1 | 17% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 3 | 50% |
| Scientists | 3 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 20 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 2 | 10% |
| Netherlands | 1 | 5% |
| Sweden | 1 | 5% |
| Unknown | 16 | 80% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 5 | 25% |
| Researcher | 4 | 20% |
| Student > Master | 3 | 15% |
| Student > Bachelor | 2 | 10% |
| Student > Doctoral Student | 1 | 5% |
| Other | 2 | 10% |
| Unknown | 3 | 15% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 7 | 35% |
| Computer Science | 3 | 15% |
| Immunology and Microbiology | 2 | 10% |
| Nursing and Health Professions | 1 | 5% |
| Biochemistry, Genetics and Molecular Biology | 1 | 5% |
| Other | 2 | 10% |
| Unknown | 4 | 20% |
Attention Score in Context
This research output has an Altmetric Attention Score of 4. 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 06 April 2014.
All research outputs
#7,130,545
of 22,747,498 outputs
Outputs from BMC Genomics
#3,375
of 10,634 outputs
Outputs of similar age
#69,707
of 221,294 outputs
Outputs of similar age from BMC Genomics
#42
of 150 outputs
Altmetric has tracked 22,747,498 research outputs across all sources so far. This one has received more attention than most of these and is in the 68th percentile.
So far Altmetric has tracked 10,634 research outputs from this source. They receive a mean Attention Score of 4.7. This one has gotten more attention than average, scoring higher than 67% 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 221,294 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 68% of its contemporaries.
We're also able to compare this research output to 150 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 70% of its contemporaries.