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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Sequence-based model of gap gene regulatory network
|
|---|---|
| Published in |
BMC Genomics, December 2014
|
| DOI | 10.1186/1471-2164-15-s12-s6 |
| Pubmed ID | |
| Authors |
Konstantin Kozlov, Vitaly Gursky, Ivan Kulakovskiy, Maria Samsonova |
| Abstract |
The detailed analysis of transcriptional regulation is crucially important for understanding biological processes. The gap gene network in Drosophila attracts large interest among researches studying mechanisms of transcriptional regulation. It implements the most upstream regulatory layer of the segmentation gene network. The knowledge of molecular mechanisms involved in gap gene regulation is far less complete than that of genetics of the system. Mathematical modeling goes beyond insights gained by genetics and molecular approaches. It allows us to reconstruct wild-type gene expression patterns in silico, infer underlying regulatory mechanism and prove its sufficiency. |
X Demographics
The data shown below were collected from the profiles of 7 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 States | 5 | 71% |
| Unknown | 2 | 29% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 5 | 71% |
| Scientists | 2 | 29% |
Mendeley readers
The data shown below were compiled from readership statistics for 22 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Argentina | 1 | 5% |
| Unknown | 21 | 95% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 7 | 32% |
| Researcher | 4 | 18% |
| Student > Master | 3 | 14% |
| Professor > Associate Professor | 2 | 9% |
| Student > Bachelor | 1 | 5% |
| Other | 3 | 14% |
| Unknown | 2 | 9% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 8 | 36% |
| Biochemistry, Genetics and Molecular Biology | 5 | 23% |
| Mathematics | 1 | 5% |
| Computer Science | 1 | 5% |
| Sports and Recreations | 1 | 5% |
| Other | 2 | 9% |
| Unknown | 4 | 18% |
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 July 2018.
All research outputs
#7,753,975
of 23,577,654 outputs
Outputs from BMC Genomics
#3,712
of 10,777 outputs
Outputs of similar age
#107,210
of 356,676 outputs
Outputs of similar age from BMC Genomics
#83
of 235 outputs
Altmetric has tracked 23,577,654 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 10,777 research outputs from this source. They receive a mean Attention Score of 4.7. This one has gotten more attention than average, scoring higher than 58% 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 356,676 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 53% of its contemporaries.
We're also able to compare this research output to 235 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 60% of its contemporaries.