You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output.
Click here to find out more.
X Demographics
Mendeley readers
Attention Score in Context
| Title |
Gene prediction in metagenomic fragments based on the SVM algorithm
|
|---|---|
| Published in |
BMC Bioinformatics, April 2013
|
| DOI | 10.1186/1471-2105-14-s5-s12 |
| Pubmed ID | |
| Authors |
Yongchu Liu, Jiangtao Guo, Gangqing Hu, Huaiqiu Zhu |
| Abstract |
Metagenomic sequencing is becoming a powerful technology for exploring micro-ogranisms from various environments, such as human body, without isolation and cultivation. Accurately identifying genes from metagenomic fragments is one of the most fundamental issues. |
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 % |
|---|---|---|
| United States | 2 | 50% |
| Germany | 1 | 25% |
| Spain | 1 | 25% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 3 | 75% |
| Members of the public | 1 | 25% |
Mendeley readers
The data shown below were compiled from readership statistics for 105 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Brazil | 2 | 2% |
| Mexico | 2 | 2% |
| United States | 2 | 2% |
| United Kingdom | 1 | <1% |
| Belgium | 1 | <1% |
| Germany | 1 | <1% |
| Unknown | 96 | 91% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 18 | 17% |
| Student > Master | 18 | 17% |
| Researcher | 17 | 16% |
| Student > Bachelor | 10 | 10% |
| Student > Doctoral Student | 6 | 6% |
| Other | 18 | 17% |
| Unknown | 18 | 17% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 33 | 31% |
| Biochemistry, Genetics and Molecular Biology | 18 | 17% |
| Computer Science | 15 | 14% |
| Immunology and Microbiology | 5 | 5% |
| Medicine and Dentistry | 5 | 5% |
| Other | 9 | 9% |
| Unknown | 20 | 19% |
Attention Score in Context
This research output has an Altmetric Attention Score of 3. 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 07 January 2014.
All research outputs
#13,051,324
of 22,738,543 outputs
Outputs from BMC Bioinformatics
#3,971
of 7,266 outputs
Outputs of similar age
#103,579
of 199,547 outputs
Outputs of similar age from BMC Bioinformatics
#74
of 135 outputs
Altmetric has tracked 22,738,543 research outputs across all sources so far. This one is in the 42nd percentile – i.e., 42% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,266 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 44th percentile – i.e., 44% 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 199,547 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 47th percentile – i.e., 47% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 135 others from the same source and published within six weeks on either side of this one. This one is in the 45th percentile – i.e., 45% of its contemporaries scored the same or lower than it.