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Characterization of an inducible promoter in different DNA copy number conditions

Overview of attention for article published in BMC Bioinformatics, March 2012
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2 X users

Citations

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27 Dimensions

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73 Mendeley
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Title
Characterization of an inducible promoter in different DNA copy number conditions
Published in
BMC Bioinformatics, March 2012
DOI 10.1186/1471-2105-13-s4-s11
Pubmed ID
Authors

Susanna Zucca, Lorenzo Pasotti, Giuliano Mazzini, Maria Gabriella Cusella De Angelis, Paolo Magni

Abstract

The bottom-up programming of living organisms to implement novel user-defined biological capabilities is one of the main goals of synthetic biology. Currently, a predominant problem connected with the construction of even simple synthetic biological systems is the unpredictability of the genetic circuitry when assembled and incorporated in living cells. Copy number, transcriptional/translational demand and toxicity of the DNA-encoded functions are some of the major factors which may lead to cell overburdening and thus to nonlinear effects on system output. It is important to disclose the linearity working boundaries of engineered biological systems when dealing with such phenomena.

X Demographics

X Demographics

The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 73 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 2 3%
United States 2 3%
Spain 1 1%
Estonia 1 1%
Unknown 67 92%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 21 29%
Researcher 17 23%
Student > Bachelor 9 12%
Lecturer 3 4%
Student > Master 3 4%
Other 10 14%
Unknown 10 14%
Readers by discipline Count As %
Agricultural and Biological Sciences 30 41%
Biochemistry, Genetics and Molecular Biology 17 23%
Engineering 8 11%
Mathematics 2 3%
Business, Management and Accounting 1 1%
Other 4 5%
Unknown 11 15%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 17 February 2014.
All research outputs
#14,143,926
of 22,664,644 outputs
Outputs from BMC Bioinformatics
#4,712
of 7,247 outputs
Outputs of similar age
#94,436
of 160,395 outputs
Outputs of similar age from BMC Bioinformatics
#50
of 82 outputs
Altmetric has tracked 22,664,644 research outputs across all sources so far. This one is in the 35th percentile – i.e., 35% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,247 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 30th percentile – i.e., 30% 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 160,395 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 38th percentile – i.e., 38% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 82 others from the same source and published within six weeks on either side of this one. This one is in the 34th percentile – i.e., 34% of its contemporaries scored the same or lower than it.