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X Demographics
Mendeley readers
Attention Score in Context
| Title |
A computational pipeline for identifying kinetic motifs to aid in the design and improvement of synthetic gene circuits
|
|---|---|
| Published in |
BMC Bioinformatics, October 2013
|
| DOI | 10.1186/1471-2105-14-s16-s5 |
| Pubmed ID | |
| Authors |
Austin WT Chiang, Ming-Jing Hwang |
| Abstract |
An increasing number of genetic components are available in several depositories of such components to facilitate synthetic biology research, but picking out those that will allow a designed circuit to achieve the specified function still requires multiple cycles of testing. Here, we addressed this problem by developing a computational pipeline to mathematically simulate a gene circuit for a comprehensive range and combination of the kinetic parameters of the biological components that constitute the gene circuit. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
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 % |
|---|---|---|
| United States | 2 | 9% |
| United Kingdom | 1 | 5% |
| Unknown | 19 | 86% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 7 | 32% |
| Researcher | 5 | 23% |
| Student > Doctoral Student | 3 | 14% |
| Student > Bachelor | 2 | 9% |
| Professor | 1 | 5% |
| Other | 2 | 9% |
| Unknown | 2 | 9% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 5 | 23% |
| Biochemistry, Genetics and Molecular Biology | 4 | 18% |
| Social Sciences | 4 | 18% |
| Computer Science | 3 | 14% |
| Medicine and Dentistry | 2 | 9% |
| Other | 2 | 9% |
| Unknown | 2 | 9% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. 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 27 February 2014.
All research outputs
#18,365,132
of 22,745,803 outputs
Outputs from BMC Bioinformatics
#6,301
of 7,268 outputs
Outputs of similar age
#158,013
of 212,098 outputs
Outputs of similar age from BMC Bioinformatics
#94
of 116 outputs
Altmetric has tracked 22,745,803 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,268 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 5th percentile – i.e., 5% 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 212,098 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 12th percentile – i.e., 12% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 116 others from the same source and published within six weeks on either side of this one. This one is in the 8th percentile – i.e., 8% of its contemporaries scored the same or lower than it.