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Mendeley readers
Attention Score in Context
| Title |
Identification of novel non-coding small RNAs from Streptococcus pneumoniae TIGR4 using high-resolution genome tiling arrays
|
|---|---|
| Published in |
BMC Genomics, June 2010
|
| DOI | 10.1186/1471-2164-11-350 |
| Pubmed ID | |
| Authors |
Ranjit Kumar, Pratik Shah, Edwin Swiatlo, Shane C Burgess, Mark L Lawrence, Bindu Nanduri |
| Abstract |
The identification of non-coding transcripts in human, mouse, and Escherichia coli has revealed their widespread occurrence and functional importance in both eukaryotic and prokaryotic life. In prokaryotes, studies have shown that non-coding transcripts participate in a broad range of cellular functions like gene regulation, stress and virulence. However, very little is known about non-coding transcripts in Streptococcus pneumoniae (pneumococcus), an obligate human respiratory pathogen responsible for significant worldwide morbidity and mortality. Tiling microarrays enable genome wide mRNA profiling as well as identification of novel transcripts at a high-resolution. |
Mendeley readers
The data shown below were compiled from readership statistics for 66 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 2% |
| Unknown | 65 | 98% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 15 | 23% |
| Researcher | 9 | 14% |
| Professor > Associate Professor | 8 | 12% |
| Student > Master | 7 | 11% |
| Student > Bachelor | 6 | 9% |
| Other | 15 | 23% |
| Unknown | 6 | 9% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 35 | 53% |
| Biochemistry, Genetics and Molecular Biology | 9 | 14% |
| Immunology and Microbiology | 4 | 6% |
| Engineering | 3 | 5% |
| Veterinary Science and Veterinary Medicine | 2 | 3% |
| Other | 6 | 9% |
| Unknown | 7 | 11% |
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 11 February 2013.
All research outputs
#7,454,951
of 22,790,780 outputs
Outputs from BMC Genomics
#3,597
of 10,647 outputs
Outputs of similar age
#34,045
of 96,101 outputs
Outputs of similar age from BMC Genomics
#17
of 44 outputs
Altmetric has tracked 22,790,780 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 10,647 research outputs from this source. They receive a mean Attention Score of 4.7. This one has gotten more attention than average, scoring higher than 59% 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 96,101 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 23rd percentile – i.e., 23% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 44 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.