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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Supervised DNA Barcodes species classification: analysis, comparisons and results
|
|---|---|
| Published in |
BioData Mining, April 2014
|
| DOI | 10.1186/1756-0381-7-4 |
| Pubmed ID | |
| Authors |
Emanuel Weitschek, Giulia Fiscon, Giovanni Felici |
| Abstract |
Specific fragments, coming from short portions of DNA (e.g., mitochondrial, nuclear, and plastid sequences), have been defined as DNA Barcode and can be used as markers for organisms of the main life kingdoms. Species classification with DNA Barcode sequences has been proven effective on different organisms. Indeed, specific gene regions have been identified as Barcode: COI in animals, rbcL and matK in plants, and ITS in fungi. The classification problem assigns an unknown specimen to a known species by analyzing its Barcode. This task has to be supported with reliable methods and algorithms. |
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 % |
|---|---|---|
| United States | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 167 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Brazil | 3 | 2% |
| Germany | 2 | 1% |
| United States | 2 | 1% |
| Malaysia | 1 | <1% |
| Korea, Republic of | 1 | <1% |
| United Kingdom | 1 | <1% |
| Colombia | 1 | <1% |
| Belgium | 1 | <1% |
| Philippines | 1 | <1% |
| Other | 0 | 0% |
| Unknown | 154 | 92% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 37 | 22% |
| Student > Master | 30 | 18% |
| Student > Ph. D. Student | 28 | 17% |
| Student > Bachelor | 14 | 8% |
| Other | 10 | 6% |
| Other | 24 | 14% |
| Unknown | 24 | 14% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 73 | 44% |
| Computer Science | 23 | 14% |
| Biochemistry, Genetics and Molecular Biology | 20 | 12% |
| Engineering | 8 | 5% |
| Earth and Planetary Sciences | 2 | 1% |
| Other | 13 | 8% |
| Unknown | 28 | 17% |
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 13 April 2014.
All research outputs
#18,370,767
of 22,753,345 outputs
Outputs from BioData Mining
#259
of 307 outputs
Outputs of similar age
#164,452
of 226,967 outputs
Outputs of similar age from BioData Mining
#5
of 6 outputs
Altmetric has tracked 22,753,345 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 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 6th percentile – i.e., 6% 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 226,967 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 6 others from the same source and published within six weeks on either side of this one.