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Mendeley readers
Attention Score in Context
| Title |
cGRNB: a web server for building combinatorial gene regulatory networks through integrated engineering of seed-matching sequence information and gene expression datasets
|
|---|---|
| Published in |
BMC Systems Biology, October 2013
|
| DOI | 10.1186/1752-0509-7-s2-s7 |
| Pubmed ID | |
| Authors |
Huayong Xu, Hui Yu, Kang Tu, Qianqian Shi, Chaochun Wei, Yuan-Yuan Li, Yi-Xue Li |
| Abstract |
We are witnessing rapid progress in the development of methodologies for building the combinatorial gene regulatory networks involving both TFs (Transcription Factors) and miRNAs (microRNAs). There are a few tools available to do these jobs but most of them are not easy to use and not accessible online. A web server is especially needed in order to allow users to upload experimental expression datasets and build combinatorial regulatory networks corresponding to their particular contexts. |
Mendeley readers
The data shown below were compiled from readership statistics for 23 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| China | 2 | 9% |
| Malaysia | 1 | 4% |
| United States | 1 | 4% |
| Brazil | 1 | 4% |
| Unknown | 18 | 78% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 7 | 30% |
| Student > Ph. D. Student | 6 | 26% |
| Student > Bachelor | 3 | 13% |
| Student > Master | 2 | 9% |
| Professor > Associate Professor | 1 | 4% |
| Other | 1 | 4% |
| Unknown | 3 | 13% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 10 | 43% |
| Computer Science | 6 | 26% |
| Engineering | 2 | 9% |
| Medicine and Dentistry | 1 | 4% |
| Biochemistry, Genetics and Molecular Biology | 1 | 4% |
| Other | 0 | 0% |
| Unknown | 3 | 13% |
Attention Score in Context
This research output has an Altmetric Attention Score of 6. 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 13 March 2014.
All research outputs
#5,726,696
of 22,747,498 outputs
Outputs from BMC Systems Biology
#189
of 1,142 outputs
Outputs of similar age
#51,294
of 210,730 outputs
Outputs of similar age from BMC Systems Biology
#4
of 27 outputs
Altmetric has tracked 22,747,498 research outputs across all sources so far. This one has received more attention than most of these and is in the 74th percentile.
So far Altmetric has tracked 1,142 research outputs from this source. They receive a mean Attention Score of 3.6. 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 210,730 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 75% of its contemporaries.
We're also able to compare this research output to 27 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 85% of its contemporaries.