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X Demographics
Mendeley readers
Attention Score in Context
| Title |
HuntMi: an efficient and taxon-specific approach in pre-miRNA identification
|
|---|---|
| Published in |
BMC Bioinformatics, March 2013
|
| DOI | 10.1186/1471-2105-14-83 |
| Pubmed ID | |
| Authors |
Adam Gudyś, Michał Wojciech Szcześniak, Marek Sikora, Izabela Makałowska |
| Abstract |
Machine learning techniques are known to be a powerful way of distinguishing microRNA hairpins from pseudo hairpins and have been applied in a number of recognised miRNA search tools. However, many current methods based on machine learning suffer from some drawbacks, including not addressing the class imbalance problem properly. It may lead to overlearning the majority class and/or incorrect assessment of classification performance. Moreover, those tools are effective for a narrow range of species, usually the model ones. This study aims at improving performance of miRNA classification procedure, extending its usability and reducing computational time. |
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 % |
|---|---|---|
| France | 1 | 50% |
| Norway | 1 | 50% |
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 88 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Canada | 2 | 2% |
| France | 1 | 1% |
| Brazil | 1 | 1% |
| Sweden | 1 | 1% |
| Turkey | 1 | 1% |
| Argentina | 1 | 1% |
| Spain | 1 | 1% |
| United States | 1 | 1% |
| Poland | 1 | 1% |
| Other | 0 | 0% |
| Unknown | 78 | 89% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 20 | 23% |
| Student > Master | 16 | 18% |
| Researcher | 11 | 13% |
| Student > Bachelor | 7 | 8% |
| Professor > Associate Professor | 6 | 7% |
| Other | 13 | 15% |
| Unknown | 15 | 17% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 27 | 31% |
| Agricultural and Biological Sciences | 26 | 30% |
| Biochemistry, Genetics and Molecular Biology | 6 | 7% |
| Engineering | 5 | 6% |
| Medicine and Dentistry | 2 | 2% |
| Other | 4 | 5% |
| Unknown | 18 | 20% |
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 05 March 2013.
All research outputs
#18,331,227
of 22,699,621 outputs
Outputs from BMC Bioinformatics
#6,289
of 7,254 outputs
Outputs of similar age
#148,262
of 194,736 outputs
Outputs of similar age from BMC Bioinformatics
#123
of 143 outputs
Altmetric has tracked 22,699,621 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 7,254 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 194,736 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 12th percentile – i.e., 12% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 143 others from the same source and published within six weeks on either side of this one. This one is in the 5th percentile – i.e., 5% of its contemporaries scored the same or lower than it.