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X Demographics
Mendeley readers
Attention Score in Context
| Title |
A comparative hidden Markov model analysis pipeline identifies proteins characteristic of cereal-infecting fungi
|
|---|---|
| Published in |
BMC Genomics, November 2013
|
| DOI | 10.1186/1471-2164-14-807 |
| Pubmed ID | |
| Authors |
Jana Sperschneider, Donald M Gardiner, Jennifer M Taylor, James K Hane, Karam B Singh, John M Manners |
| Abstract |
Fungal pathogens cause devastating losses in economically important cereal crops by utilising pathogen proteins to infect host plants. Secreted pathogen proteins are referred to as effectors and have thus far been identified by selecting small, cysteine-rich peptides from the secretome despite increasing evidence that not all effectors share these attributes. |
X Demographics
The data shown below were collected from the profiles of 8 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Canada | 2 | 25% |
| Germany | 2 | 25% |
| Australia | 1 | 13% |
| United States | 1 | 13% |
| Netherlands | 1 | 13% |
| Unknown | 1 | 13% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 6 | 75% |
| Members of the public | 2 | 25% |
Mendeley readers
The data shown below were compiled from readership statistics for 89 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 4 | 4% |
| Netherlands | 1 | 1% |
| Australia | 1 | 1% |
| United Kingdom | 1 | 1% |
| Brazil | 1 | 1% |
| China | 1 | 1% |
| Taiwan | 1 | 1% |
| Unknown | 79 | 89% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 25 | 28% |
| Researcher | 24 | 27% |
| Student > Master | 8 | 9% |
| Student > Bachelor | 6 | 7% |
| Student > Doctoral Student | 5 | 6% |
| Other | 10 | 11% |
| Unknown | 11 | 12% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 53 | 60% |
| Biochemistry, Genetics and Molecular Biology | 15 | 17% |
| Arts and Humanities | 2 | 2% |
| Computer Science | 2 | 2% |
| Nursing and Health Professions | 1 | 1% |
| Other | 2 | 2% |
| Unknown | 14 | 16% |
Attention Score in Context
This research output has an Altmetric Attention Score of 4. 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 17 July 2016.
All research outputs
#7,355,930
of 25,373,627 outputs
Outputs from BMC Genomics
#3,109
of 11,244 outputs
Outputs of similar age
#79,415
of 315,467 outputs
Outputs of similar age from BMC Genomics
#54
of 216 outputs
Altmetric has tracked 25,373,627 research outputs across all sources so far. This one has received more attention than most of these and is in the 69th percentile.
So far Altmetric has tracked 11,244 research outputs from this source. They receive a mean Attention Score of 4.8. This one has gotten more attention than average, scoring higher than 70% of its peers.
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 315,467 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 73% of its contemporaries.
We're also able to compare this research output to 216 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 74% of its contemporaries.