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Mendeley readers
Attention Score in Context
| Title |
Simultaneous prediction of transcription factor binding sites in a group of prokaryotic genomes
|
|---|---|
| Published in |
BMC Bioinformatics, July 2010
|
| DOI | 10.1186/1471-2105-11-397 |
| Pubmed ID | |
| Authors |
Shaoqiang Zhang, Shan Li, Phuc T Pham, Zhengchang Su |
| Abstract |
Our current understanding of transcription factor binding sites (TFBSs) in sequenced prokaryotic genomes is very limited due to the lack of an accurate and efficient computational method for the prediction of TFBSs at a genome scale. In an attempt to change this situation, we have recently developed a comparative genomics based algorithm called GLECLUBS for de novo genome-wide prediction of TFBSs in a target genome. Although GLECLUBS has achieved rather high prediction accuracy of TFBSs in a target genome, it is still not efficient enough to be applied to all the sequenced prokaryotic genomes. |
Mendeley readers
The data shown below were compiled from readership statistics for 40 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 4 | 10% |
| Colombia | 1 | 3% |
| France | 1 | 3% |
| Spain | 1 | 3% |
| United Kingdom | 1 | 3% |
| Greece | 1 | 3% |
| Poland | 1 | 3% |
| Unknown | 30 | 75% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 14 | 35% |
| Student > Ph. D. Student | 6 | 15% |
| Professor > Associate Professor | 4 | 10% |
| Student > Bachelor | 3 | 8% |
| Student > Postgraduate | 3 | 8% |
| Other | 8 | 20% |
| Unknown | 2 | 5% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 24 | 60% |
| Biochemistry, Genetics and Molecular Biology | 7 | 18% |
| Computer Science | 3 | 8% |
| Environmental Science | 1 | 3% |
| Immunology and Microbiology | 1 | 3% |
| Other | 2 | 5% |
| Unknown | 2 | 5% |
Attention Score in Context
This research output has an Altmetric Attention Score of 3. 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 23 March 2011.
All research outputs
#12,846,160
of 22,649,029 outputs
Outputs from BMC Bioinformatics
#3,776
of 7,234 outputs
Outputs of similar age
#71,835
of 93,939 outputs
Outputs of similar age from BMC Bioinformatics
#34
of 56 outputs
Altmetric has tracked 22,649,029 research outputs across all sources so far. This one is in the 42nd percentile – i.e., 42% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,234 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one is in the 45th percentile – i.e., 45% 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 93,939 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 23rd percentile – i.e., 23% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 56 others from the same source and published within six weeks on either side of this one. This one is in the 33rd percentile – i.e., 33% of its contemporaries scored the same or lower than it.