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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Performance of genetic programming optimised Bowtie2 on genome comparison and analytic testing (GCAT) benchmarks
|
|---|---|
| Published in |
BioData Mining, January 2015
|
| DOI | 10.1186/s13040-014-0034-0 |
| Pubmed ID | |
| Authors |
W B Langdon |
| Abstract |
Genetic studies are increasingly based on short noisy next generation scanners. Typically complete DNA sequences are assembled by matching short NextGen sequences against reference genomes. Despite considerable algorithmic gains since the turn of the millennium, matching both single ended and paired end strings to a reference remains computationally demanding. Further tailoring Bioinformatics tools to each new task or scanner remains highly skilled and labour intensive. With this in mind, we recently demonstrated a genetic programming based automated technique which generated a version of the state-of-the-art alignment tool Bowtie2 which was considerably faster on short sequences produced by a scanner at the Broad Institute and released as part of The Thousand Genome Project. |
X Demographics
The data shown below were collected from the profiles of 2 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 States | 2 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 50% |
| Members of the public | 1 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 141 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 2 | 1% |
| United States | 1 | <1% |
| Unknown | 138 | 98% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 23 | 16% |
| Student > Ph. D. Student | 21 | 15% |
| Student > Bachelor | 19 | 13% |
| Student > Master | 15 | 11% |
| Student > Doctoral Student | 6 | 4% |
| Other | 19 | 13% |
| Unknown | 38 | 27% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 40 | 28% |
| Agricultural and Biological Sciences | 24 | 17% |
| Computer Science | 12 | 9% |
| Immunology and Microbiology | 6 | 4% |
| Engineering | 5 | 4% |
| Other | 12 | 9% |
| Unknown | 42 | 30% |
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 27 January 2015.
All research outputs
#15,314,171
of 22,776,824 outputs
Outputs from BioData Mining
#225
of 307 outputs
Outputs of similar age
#208,649
of 352,269 outputs
Outputs of similar age from BioData Mining
#10
of 12 outputs
Altmetric has tracked 22,776,824 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 307 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.7. This one is in the 19th percentile – i.e., 19% 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 352,269 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 31st percentile – i.e., 31% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 12 others from the same source and published within six weeks on either side of this one. This one is in the 8th percentile – i.e., 8% of its contemporaries scored the same or lower than it.