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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Comparison study on statistical features of predicted secondary structures for protein structural class prediction: From content to position
|
|---|---|
| Published in |
BMC Bioinformatics, May 2013
|
| DOI | 10.1186/1471-2105-14-152 |
| Pubmed ID | |
| Authors |
Qi Dai, Yan Li, Xiaoqing Liu, Yuhua Yao, Yunjie Cao, Pingan He |
| Abstract |
Many content-based statistical features of secondary structural elements (CBF-PSSEs) have been proposed and achieved promising results in protein structural class prediction, but until now position distribution of the successive occurrences of an element in predicted secondary structure sequences hasn't been used. It is necessary to extract some appropriate position-based features of the secondary structural elements for prediction task. |
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 % |
|---|---|---|
| Norway | 1 | 50% |
| United States | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 50% |
| Scientists | 1 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 22 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Iran, Islamic Republic of | 1 | 5% |
| Germany | 1 | 5% |
| Unknown | 20 | 91% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 6 | 27% |
| Student > Bachelor | 4 | 18% |
| Researcher | 3 | 14% |
| Lecturer | 1 | 5% |
| Other | 1 | 5% |
| Other | 3 | 14% |
| Unknown | 4 | 18% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 8 | 36% |
| Agricultural and Biological Sciences | 3 | 14% |
| Biochemistry, Genetics and Molecular Biology | 3 | 14% |
| Engineering | 2 | 9% |
| Medicine and Dentistry | 1 | 5% |
| Other | 0 | 0% |
| Unknown | 5 | 23% |
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 04 May 2013.
All research outputs
#17,687,671
of 22,709,015 outputs
Outputs from BMC Bioinformatics
#5,917
of 7,256 outputs
Outputs of similar age
#138,467
of 192,833 outputs
Outputs of similar age from BMC Bioinformatics
#103
of 124 outputs
Altmetric has tracked 22,709,015 research outputs across all sources so far. This one is in the 19th percentile – i.e., 19% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,256 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 13th percentile – i.e., 13% 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 192,833 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 24th percentile – i.e., 24% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 124 others from the same source and published within six weeks on either side of this one. This one is in the 7th percentile – i.e., 7% of its contemporaries scored the same or lower than it.