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X Demographics
Mendeley readers
Attention Score in Context
| Title |
TIGAR2: sensitive and accurate estimation of transcript isoform expression with longer RNA-Seq reads
|
|---|---|
| Published in |
BMC Genomics, December 2014
|
| DOI | 10.1186/1471-2164-15-s10-s5 |
| Pubmed ID | |
| Authors |
Naoki Nariai, Kaname Kojima, Takahiro Mimori, Yukuto Sato, Yosuke Kawai, Yumi Yamaguchi-Kabata, Masao Nagasaki |
| Abstract |
High-throughput RNA sequencing (RNA-Seq) enables quantification and identification of transcripts at single-base resolution. Recently, longer sequence reads become available thanks to the development of new types of sequencing technologies as well as improvements in chemical reagents for the Next Generation Sequencers. Although several computational methods have been proposed for quantifying gene expression levels from RNA-Seq data, they are not sufficiently optimized for longer reads (e.g. > 250 bp). |
X Demographics
The data shown below were collected from the profiles of 6 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| India | 2 | 33% |
| France | 1 | 17% |
| Unknown | 3 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 4 | 67% |
| Scientists | 2 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 61 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 2 | 3% |
| Italy | 1 | 2% |
| Germany | 1 | 2% |
| Japan | 1 | 2% |
| Czechia | 1 | 2% |
| Unknown | 55 | 90% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 18 | 30% |
| Researcher | 12 | 20% |
| Student > Bachelor | 5 | 8% |
| Professor > Associate Professor | 5 | 8% |
| Other | 4 | 7% |
| Other | 8 | 13% |
| Unknown | 9 | 15% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 24 | 39% |
| Computer Science | 6 | 10% |
| Engineering | 5 | 8% |
| Biochemistry, Genetics and Molecular Biology | 5 | 8% |
| Medicine and Dentistry | 3 | 5% |
| Other | 7 | 11% |
| Unknown | 11 | 18% |
Attention Score in Context
This research output has an Altmetric Attention Score of 13. 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 06 July 2017.
All research outputs
#2,328,526
of 22,776,824 outputs
Outputs from BMC Genomics
#716
of 10,643 outputs
Outputs of similar age
#34,499
of 356,570 outputs
Outputs of similar age from BMC Genomics
#16
of 234 outputs
Altmetric has tracked 22,776,824 research outputs across all sources so far. Compared to these this one has done well and is in the 89th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 10,643 research outputs from this source. They receive a mean Attention Score of 4.7. This one has done particularly well, scoring higher than 93% 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 356,570 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 90% of its contemporaries.
We're also able to compare this research output to 234 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 93% of its contemporaries.