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Attention Score in Context
| Title |
Thermodynamic modeling of transcription: sensitivity analysis differentiates biological mechanism from mathematical model-induced effects
|
|---|---|
| Published in |
BMC Systems Biology, October 2010
|
| DOI | 10.1186/1752-0509-4-142 |
| Pubmed ID | |
| Authors |
Jacqueline M Dresch, Xiaozhou Liu, David N Arnosti, Ahmet Ay |
| Abstract |
Quantitative models of gene expression generate parameter values that can shed light on biological features such as transcription factor activity, cooperativity, and local effects of repressors. An important element in such investigations is sensitivity analysis, which determines how strongly a model's output reacts to variations in parameter values. Parameters of low sensitivity may not be accurately estimated, leading to unwarranted conclusions. Low sensitivity may reflect the nature of the biological data, or it may be a result of the model structure. Here, we focus on the analysis of thermodynamic models, which have been used extensively to analyze gene transcription. Extracted parameter values have been interpreted biologically, but until now little attention has been given to parameter sensitivity in this context. |
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 % |
|---|---|---|
| Canada | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 62 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 3 | 5% |
| Italy | 1 | 2% |
| France | 1 | 2% |
| Mexico | 1 | 2% |
| Brazil | 1 | 2% |
| Unknown | 55 | 89% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 22 | 35% |
| Researcher | 13 | 21% |
| Student > Doctoral Student | 5 | 8% |
| Student > Bachelor | 4 | 6% |
| Professor | 4 | 6% |
| Other | 9 | 15% |
| Unknown | 5 | 8% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 23 | 37% |
| Biochemistry, Genetics and Molecular Biology | 9 | 15% |
| Computer Science | 7 | 11% |
| Mathematics | 4 | 6% |
| Medicine and Dentistry | 4 | 6% |
| Other | 9 | 15% |
| Unknown | 6 | 10% |
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 26 July 2013.
All research outputs
#18,342,133
of 22,715,151 outputs
Outputs from BMC Systems Biology
#834
of 1,142 outputs
Outputs of similar age
#88,680
of 99,405 outputs
Outputs of similar age from BMC Systems Biology
#11
of 12 outputs
Altmetric has tracked 22,715,151 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 1,142 research outputs from this source. They receive a mean Attention Score of 3.6. This one is in the 11th percentile – i.e., 11% of its peers scored the same or lower than it.
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We're also able to compare this research output to 12 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.