| Title |
Prediction of novel long non-coding RNAs based on RNA-Seq data of mouse Klf1 knockout study
|
|---|---|
| Published in |
BMC Bioinformatics, December 2012
|
| DOI | 10.1186/1471-2105-13-331 |
| Pubmed ID | |
| Authors |
Lei Sun, Zhihua Zhang, Timothy L Bailey, Andrew C Perkins, Michael R Tallack, Zhao Xu, Hui Liu |
| Abstract |
Study on long non-coding RNAs (lncRNAs) has been promoted by high-throughput RNA sequencing (RNA-Seq). However, it is still not trivial to identify lncRNAs from the RNA-Seq data and it remains a challenge to uncover their functions. |
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 | 2 | 40% |
| France | 1 | 20% |
| Japan | 1 | 20% |
| Norway | 1 | 20% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 3 | 60% |
| Members of the public | 2 | 40% |
Mendeley readers
The data shown below were compiled from readership statistics for 240 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 4 | 2% |
| France | 2 | <1% |
| India | 2 | <1% |
| United Kingdom | 2 | <1% |
| Canada | 2 | <1% |
| Australia | 1 | <1% |
| Brazil | 1 | <1% |
| Norway | 1 | <1% |
| Denmark | 1 | <1% |
| Other | 5 | 2% |
| Unknown | 219 | 91% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 68 | 28% |
| Student > Ph. D. Student | 65 | 27% |
| Student > Master | 35 | 15% |
| Student > Bachelor | 18 | 8% |
| Other | 10 | 4% |
| Other | 28 | 12% |
| Unknown | 16 | 7% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 120 | 50% |
| Biochemistry, Genetics and Molecular Biology | 58 | 24% |
| Computer Science | 20 | 8% |
| Medicine and Dentistry | 5 | 2% |
| Neuroscience | 3 | 1% |
| Other | 11 | 5% |
| Unknown | 23 | 10% |
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
#3,238,037
of 22,689,790 outputs
Outputs from BMC Bioinformatics
#1,192
of 7,252 outputs
Outputs of similar age
#33,887
of 278,829 outputs
Outputs of similar age from BMC Bioinformatics
#18
of 138 outputs
Altmetric has tracked 22,689,790 research outputs across all sources so far. Compared to these this one has done well and is in the 85th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,252 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one has done well, scoring higher than 83% 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 278,829 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 138 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.