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X Demographics
Mendeley readers
Attention Score in Context
| Title |
XSAnno: a framework for building ortholog models in cross-species transcriptome comparisons
|
|---|---|
| Published in |
BMC Genomics, May 2014
|
| DOI | 10.1186/1471-2164-15-343 |
| Pubmed ID | |
| Authors |
Ying Zhu, Mingfeng Li, André MM Sousa, Nenad Šestan |
| Abstract |
The accurate characterization of RNA transcripts and expression levels across species is critical for understanding transcriptome evolution. As available RNA-seq data accumulate rapidly, there is a great demand for tools that build gene annotations for cross-species RNA-seq analysis. However, prevailing methods of ortholog annotation for RNA-seq analysis between closely-related species do not take inter-species variation in mappability into consideration. |
X Demographics
The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| France | 1 | 33% |
| Germany | 1 | 33% |
| Unknown | 1 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 2 | 67% |
| Members of the public | 1 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 93 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 5 | 5% |
| Brazil | 1 | 1% |
| Netherlands | 1 | 1% |
| Taiwan | 1 | 1% |
| United Kingdom | 1 | 1% |
| Unknown | 84 | 90% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 23 | 25% |
| Student > Ph. D. Student | 19 | 20% |
| Student > Master | 11 | 12% |
| Other | 7 | 8% |
| Professor > Associate Professor | 5 | 5% |
| Other | 15 | 16% |
| Unknown | 13 | 14% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 46 | 49% |
| Biochemistry, Genetics and Molecular Biology | 13 | 14% |
| Neuroscience | 7 | 8% |
| Medicine and Dentistry | 4 | 4% |
| Computer Science | 3 | 3% |
| Other | 3 | 3% |
| Unknown | 17 | 18% |
Attention Score in Context
This research output has an Altmetric Attention Score of 14. 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 22 September 2014.
All research outputs
#2,227,540
of 22,755,127 outputs
Outputs from BMC Genomics
#664
of 10,637 outputs
Outputs of similar age
#23,770
of 227,501 outputs
Outputs of similar age from BMC Genomics
#12
of 196 outputs
Altmetric has tracked 22,755,127 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 90th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 10,637 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 227,501 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 89% of its contemporaries.
We're also able to compare this research output to 196 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.