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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Transcription start sites at the end of protein-coding genes
|
|---|---|
| Published in |
Human Genomics, March 2018
|
| DOI | 10.1186/s40246-018-0146-6 |
| Pubmed ID | |
| Authors |
Ming-Yu Huang, Ji-Long Liu |
| Abstract |
Previous studies demonstrated that massive induction of transcriptional readthrough generates downstream of gene-containing transcripts (DoGs) in cells under stress condition. Here, we analyzed TSS-seq (transcription start site sequencing) data from the DBTSS database. We investigated TSS tags at the end of gene for all pan-stress and untreated-cell DoGs, in comparison with expression-matched non-DoGs. We observed significantly more TSS tags at the end of pan-stress and untreated-cell DoG genes than non-DoG genes, even though their TSS tags in the promoter is the same. Importantly, the median value of TSS tags at gene end normalized to gene promoter is significantly higher than the median expression ratio of short DoG to host gene and of long DoG to host gene. Our results indicate that downstream overlapping long non-coding RNAs derived from the TSS at the gene end may be an important source of DoGs. |
X Demographics
The data shown below were collected from the profiles of 2 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 Kingdom | 1 | 50% |
| United States | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 14 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 14 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 5 | 36% |
| Student > Ph. D. Student | 4 | 29% |
| Student > Doctoral Student | 1 | 7% |
| Student > Master | 1 | 7% |
| Other | 1 | 7% |
| Other | 0 | 0% |
| Unknown | 2 | 14% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 7 | 50% |
| Agricultural and Biological Sciences | 2 | 14% |
| Pharmacology, Toxicology and Pharmaceutical Science | 1 | 7% |
| Medicine and Dentistry | 1 | 7% |
| Neuroscience | 1 | 7% |
| Other | 0 | 0% |
| Unknown | 2 | 14% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. 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 24 April 2018.
All research outputs
#15,745,807
of 25,382,440 outputs
Outputs from Human Genomics
#333
of 564 outputs
Outputs of similar age
#196,847
of 351,776 outputs
Outputs of similar age from Human Genomics
#15
of 19 outputs
Altmetric has tracked 25,382,440 research outputs across all sources so far. This one is in the 37th percentile – i.e., 37% of other outputs scored the same or lower than it.
So far Altmetric has tracked 564 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.0. This one is in the 38th percentile – i.e., 38% of its peers scored the same or lower than it.
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 351,776 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 42nd percentile – i.e., 42% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 19 others from the same source and published within six weeks on either side of this one. This one is in the 21st percentile – i.e., 21% of its contemporaries scored the same or lower than it.