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Computational codon optimization of synthetic gene for protein expression

Overview of attention for article published in BMC Systems Biology, January 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 (84th percentile)
  • High Attention Score compared to outputs of the same age and source (91st percentile)

Mentioned by

twitter
7 tweeters
patent
2 patents

Citations

dimensions_citation
63 Dimensions

Readers on

mendeley
226 Mendeley
citeulike
2 CiteULike
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Title
Computational codon optimization of synthetic gene for protein expression
Published in
BMC Systems Biology, January 2012
DOI 10.1186/1752-0509-6-134
Pubmed ID
Authors

Bevan Chung, Dong-Yup Lee

Abstract

The construction of customized nucleic acid sequences allows us to have greater flexibility in gene design for recombinant protein expression. Among the various parameters considered for such DNA sequence design, individual codon usage (ICU) has been implicated as one of the most crucial factors affecting mRNA translational efficiency. However, previous works have also reported the significant influence of codon pair usage, also known as codon context (CC), on the level of protein expression.

Twitter Demographics

The data shown below were collected from the profiles of 7 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 226 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 2 <1%
France 1 <1%
Uruguay 1 <1%
Austria 1 <1%
Australia 1 <1%
India 1 <1%
United Kingdom 1 <1%
Canada 1 <1%
Japan 1 <1%
Other 1 <1%
Unknown 215 95%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 58 26%
Researcher 44 19%
Student > Master 31 14%
Student > Bachelor 19 8%
Student > Doctoral Student 10 4%
Other 41 18%
Unknown 23 10%
Readers by discipline Count As %
Agricultural and Biological Sciences 103 46%
Biochemistry, Genetics and Molecular Biology 48 21%
Computer Science 17 8%
Chemistry 6 3%
Engineering 6 3%
Other 19 8%
Unknown 27 12%

Attention Score in Context

This research output has an Altmetric Attention Score of 9. 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 21 October 2021.
All research outputs
#3,566,860
of 22,307,302 outputs
Outputs from BMC Systems Biology
#103
of 1,142 outputs
Outputs of similar age
#26,259
of 171,889 outputs
Outputs of similar age from BMC Systems Biology
#7
of 69 outputs
Altmetric has tracked 22,307,302 research outputs across all sources so far. Compared to these this one has done well and is in the 83rd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,142 research outputs from this source. They receive a mean Attention Score of 3.6. This one has done particularly well, scoring higher than 90% 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 171,889 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 84% of its contemporaries.
We're also able to compare this research output to 69 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 91% of its contemporaries.