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Automated Selection of Synthetic Biology Parts for Genetic Regulatory Networks

Overview of attention for article published in ACS Synthetic Biology, July 2012
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (87th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (60th percentile)

Mentioned by

blogs
1 blog
twitter
4 X users
facebook
1 Facebook page
googleplus
1 Google+ user

Citations

dimensions_citation
53 Dimensions

Readers on

mendeley
98 Mendeley
citeulike
2 CiteULike
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Title
Automated Selection of Synthetic Biology Parts for Genetic Regulatory Networks
Published in
ACS Synthetic Biology, July 2012
DOI 10.1021/sb300032y
Pubmed ID
Authors

Fusun Yaman, Swapnil Bhatia, Aaron Adler, Douglas Densmore, Jacob Beal

Abstract

Raising the level of abstraction for synthetic biology design requires solving several challenging problems, including mapping abstract designs to DNA sequences. In this paper we present the first formalism and algorithms to address this problem. The key steps of this transformation are feature matching, signal matching, and part matching. Feature matching ensures that the mapping satisfies the regulatory relationships in the abstract design. Signal matching ensures that the expression levels of functional units are compatible. Finally, part matching finds a DNA part sequence that can implement the design. Our software tool MatchMaker implements these three steps.

X Demographics

X Demographics

The data shown below were collected from the profiles of 4 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 98 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 4 4%
Belgium 3 3%
United Kingdom 2 2%
India 1 1%
Austria 1 1%
France 1 1%
Unknown 86 88%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 36 37%
Researcher 20 20%
Student > Master 11 11%
Student > Bachelor 6 6%
Professor 5 5%
Other 13 13%
Unknown 7 7%
Readers by discipline Count As %
Agricultural and Biological Sciences 33 34%
Biochemistry, Genetics and Molecular Biology 17 17%
Engineering 14 14%
Computer Science 13 13%
Immunology and Microbiology 2 2%
Other 8 8%
Unknown 11 11%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 11. 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 10 October 2014.
All research outputs
#3,343,717
of 25,377,790 outputs
Outputs from ACS Synthetic Biology
#811
of 2,904 outputs
Outputs of similar age
#21,995
of 178,724 outputs
Outputs of similar age from ACS Synthetic Biology
#10
of 28 outputs
Altmetric has tracked 25,377,790 research outputs across all sources so far. Compared to these this one has done well and is in the 86th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,904 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.3. This one has gotten more attention than average, scoring higher than 71% 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 178,724 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 87% of its contemporaries.
We're also able to compare this research output to 28 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.