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X Demographics
Mendeley readers
Attention Score in Context
| Title |
iSeeRNA: identification of long intergenic non-coding RNA transcripts from transcriptome sequencing data
|
|---|---|
| Published in |
BMC Genomics, February 2013
|
| DOI | 10.1186/1471-2164-14-s2-s7 |
| Pubmed ID | |
| Authors |
Kun Sun, Xiaona Chen, Peiyong Jiang, Xiaofeng Song, Huating Wang, Hao Sun |
| Abstract |
Long intergenic non-coding RNAs (lincRNAs) are emerging as a novel class of non-coding RNAs and potent gene regulators. High-throughput RNA-sequencing combined with de novo assembly promises quantity discovery of novel transcripts. However, the identification of lincRNAs from thousands of assembled transcripts is still challenging due to the difficulties of separating them from protein coding transcripts (PCTs). |
X Demographics
The data shown below were collected from the profiles of 5 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 | 1 | 20% |
| Japan | 1 | 20% |
| Germany | 1 | 20% |
| France | 1 | 20% |
| Unknown | 1 | 20% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 4 | 80% |
| Members of the public | 1 | 20% |
Mendeley readers
The data shown below were compiled from readership statistics for 199 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 3 | 2% |
| India | 3 | 2% |
| Germany | 1 | <1% |
| France | 1 | <1% |
| Italy | 1 | <1% |
| Canada | 1 | <1% |
| Taiwan | 1 | <1% |
| China | 1 | <1% |
| Korea, Republic of | 1 | <1% |
| Other | 1 | <1% |
| Unknown | 185 | 93% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 50 | 25% |
| Student > Ph. D. Student | 40 | 20% |
| Student > Master | 22 | 11% |
| Student > Bachelor | 16 | 8% |
| Professor > Associate Professor | 12 | 6% |
| Other | 28 | 14% |
| Unknown | 31 | 16% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 66 | 33% |
| Biochemistry, Genetics and Molecular Biology | 41 | 21% |
| Computer Science | 22 | 11% |
| Medicine and Dentistry | 8 | 4% |
| Engineering | 7 | 4% |
| Other | 19 | 10% |
| Unknown | 36 | 18% |
Attention Score in Context
This research output has an Altmetric Attention Score of 10. 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 21 February 2013.
All research outputs
#3,076,664
of 22,696,971 outputs
Outputs from BMC Genomics
#1,148
of 10,616 outputs
Outputs of similar age
#37,177
of 307,673 outputs
Outputs of similar age from BMC Genomics
#49
of 357 outputs
Altmetric has tracked 22,696,971 research outputs across all sources so far. Compared to these this one has done well and is in the 86th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 10,616 research outputs from this source. They receive a mean Attention Score of 4.7. This one has done well, scoring higher than 89% 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 307,673 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 87% of its contemporaries.
We're also able to compare this research output to 357 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 86% of its contemporaries.