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.
Mendeley readers
Attention Score in Context
| Title |
Extension of Lander-Waterman theory for sequencing filtered DNA libraries
|
|---|---|
| Published in |
BMC Bioinformatics, October 2005
|
| DOI | 10.1186/1471-2105-6-245 |
| Pubmed ID | |
| Authors |
Michael C Wendl, W Brad Barbazuk |
| Abstract |
The degree to which conventional DNA sequencing techniques will be successful for highly repetitive genomes is unclear. Investigators are therefore considering various filtering methods to select against high-copy sequence in DNA clone libraries. The standard model for random sequencing, Lander-Waterman theory, does not account for two important issues in such libraries, discontinuities and position-based sampling biases (the so-called "edge effect"). We report an extension of the theory for analyzing such configurations. |
Mendeley readers
The data shown below were compiled from readership statistics for 60 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| France | 2 | 3% |
| United States | 2 | 3% |
| Lithuania | 1 | 2% |
| Netherlands | 1 | 2% |
| Mexico | 1 | 2% |
| Canada | 1 | 2% |
| Unknown | 52 | 87% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 19 | 32% |
| Student > Ph. D. Student | 13 | 22% |
| Student > Master | 6 | 10% |
| Other | 5 | 8% |
| Professor | 3 | 5% |
| Other | 10 | 17% |
| Unknown | 4 | 7% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 33 | 55% |
| Biochemistry, Genetics and Molecular Biology | 9 | 15% |
| Computer Science | 6 | 10% |
| Engineering | 2 | 3% |
| Mathematics | 1 | 2% |
| Other | 2 | 3% |
| Unknown | 7 | 12% |
Attention Score in Context
This research output has an Altmetric Attention Score of 3. 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 07 November 2020.
All research outputs
#7,454,298
of 22,789,076 outputs
Outputs from BMC Bioinformatics
#3,023
of 7,279 outputs
Outputs of similar age
#20,343
of 58,502 outputs
Outputs of similar age from BMC Bioinformatics
#6
of 16 outputs
Altmetric has tracked 22,789,076 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,279 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 gotten more attention than average, scoring higher than 50% 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 58,502 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 14th percentile – i.e., 14% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 16 others from the same source and published within six weeks on either side of this one. This one is in the 31st percentile – i.e., 31% of its contemporaries scored the same or lower than it.