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X Demographics
Mendeley readers
Attention Score in Context
| Title |
A comparison study on feature selection of DNA structural properties for promoter prediction
|
|---|---|
| Published in |
BMC Bioinformatics, January 2012
|
| DOI | 10.1186/1471-2105-13-4 |
| Pubmed ID | |
| Authors |
Yanglan Gan, Jihong Guan, Shuigeng Zhou |
| Abstract |
Promoter prediction is an integrant step for understanding gene regulation and annotating genomes. Traditional promoter analysis is mainly based on sequence compositional features. Recently, many kinds of structural features have been employed in promoter prediction. However, considering the high-dimensionality and overfitting problems, it is unfeasible to utilize all available features for promoter prediction. Thus it is necessary to choose some appropriate features for the prediction task. |
X Demographics
The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Switzerland | 1 | 25% |
| Unknown | 3 | 75% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 3 | 75% |
| Scientists | 1 | 25% |
Mendeley readers
The data shown below were compiled from readership statistics for 63 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| India | 2 | 3% |
| Denmark | 1 | 2% |
| France | 1 | 2% |
| Australia | 1 | 2% |
| Unknown | 58 | 92% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 15 | 24% |
| Researcher | 12 | 19% |
| Student > Postgraduate | 6 | 10% |
| Professor | 4 | 6% |
| Student > Doctoral Student | 4 | 6% |
| Other | 10 | 16% |
| Unknown | 12 | 19% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 22 | 35% |
| Computer Science | 12 | 19% |
| Biochemistry, Genetics and Molecular Biology | 8 | 13% |
| Chemistry | 3 | 5% |
| Arts and Humanities | 1 | 2% |
| Other | 3 | 5% |
| Unknown | 14 | 22% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. 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 12 January 2012.
All research outputs
#13,359,365
of 22,661,413 outputs
Outputs from BMC Bioinformatics
#4,187
of 7,241 outputs
Outputs of similar age
#144,609
of 241,947 outputs
Outputs of similar age from BMC Bioinformatics
#53
of 91 outputs
Altmetric has tracked 22,661,413 research outputs across all sources so far. This one is in the 39th percentile – i.e., 39% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,241 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 38th percentile – i.e., 38% 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 241,947 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 38th percentile – i.e., 38% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 91 others from the same source and published within six weeks on either side of this one. This one is in the 41st percentile – i.e., 41% of its contemporaries scored the same or lower than it.