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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Learning to rank-based gene summary extraction
|
|---|---|
| Published in |
BMC Bioinformatics, November 2014
|
| DOI | 10.1186/1471-2105-15-s12-s10 |
| Pubmed ID | |
| Authors |
Yue Shang, Huihui Hao, Jiajin Wu, Hongfei Lin |
| Abstract |
In recent years, the biomedical literature has been growing rapidly. These articles provide a large amount of information about proteins, genes and their interactions. Reading such a huge amount of literature is a tedious task for researchers to gain knowledge about a gene. As a result, it is significant for biomedical researchers to have a quick understanding of the query concept by integrating its relevant resources. |
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 % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 13 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 13 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 4 | 31% |
| Researcher | 3 | 23% |
| Student > Doctoral Student | 1 | 8% |
| Unspecified | 1 | 8% |
| Student > Bachelor | 1 | 8% |
| Other | 1 | 8% |
| Unknown | 2 | 15% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 5 | 38% |
| Unspecified | 1 | 8% |
| Arts and Humanities | 1 | 8% |
| Medicine and Dentistry | 1 | 8% |
| Engineering | 1 | 8% |
| Other | 0 | 0% |
| Unknown | 4 | 31% |
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 December 2014.
All research outputs
#15,311,799
of 22,772,779 outputs
Outputs from BMC Bioinformatics
#5,373
of 7,276 outputs
Outputs of similar age
#153,152
of 262,799 outputs
Outputs of similar age from BMC Bioinformatics
#101
of 144 outputs
Altmetric has tracked 22,772,779 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 7,276 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 18th percentile – i.e., 18% 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 262,799 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 32nd percentile – i.e., 32% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 144 others from the same source and published within six weeks on either side of this one. This one is in the 22nd percentile – i.e., 22% of its contemporaries scored the same or lower than it.