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A bioinformatics approach for identifying transgene insertion sites using whole genome sequencing data

Overview of attention for article published in BMC Biotechnology, August 2017
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (67th percentile)

Mentioned by

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3 tweeters
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1 patent

Citations

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26 Dimensions

Readers on

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68 Mendeley
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Title
A bioinformatics approach for identifying transgene insertion sites using whole genome sequencing data
Published in
BMC Biotechnology, August 2017
DOI 10.1186/s12896-017-0386-x
Pubmed ID
Authors

Doori Park, Su-Hyun Park, Yong Wook Ban, Youn Shic Kim, Kyoung-Cheul Park, Nam-Soo Kim, Ju-Kon Kim, Ik-Young Choi

Abstract

Genetically modified crops (GM crops) have been developed to improve the agricultural traits of modern crop cultivars. Safety assessments of GM crops are of paramount importance in research at developmental stages and before releasing transgenic plants into the marketplace. Sequencing technology is developing rapidly, with higher output and labor efficiencies, and will eventually replace existing methods for the molecular characterization of genetically modified organisms. To detect the transgenic insertion locations in the three GM rice gnomes, Illumina sequencing reads are mapped and classified to the rice genome and plasmid sequence. The both mapped reads are classified to characterize the junction site between plant and transgene sequence by sequence alignment. Herein, we present a next generation sequencing (NGS)-based molecular characterization method, using transgenic rice plants SNU-Bt9-5, SNU-Bt9-30, and SNU-Bt9-109. Specifically, using bioinformatics tools, we detected the precise insertion locations and copy numbers of transfer DNA, genetic rearrangements, and the absence of backbone sequences, which were equivalent to results obtained from Southern blot analyses. NGS methods have been suggested as an effective means of characterizing and detecting transgenic insertion locations in genomes. Our results demonstrate the use of a combination of NGS technology and bioinformatics approaches that offers cost- and time-effective methods for assessing the safety of transgenic plants.

Twitter Demographics

The data shown below were collected from the profiles of 3 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 68 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 68 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 13 19%
Researcher 13 19%
Student > Ph. D. Student 12 18%
Student > Postgraduate 4 6%
Student > Master 4 6%
Other 6 9%
Unknown 16 24%
Readers by discipline Count As %
Agricultural and Biological Sciences 27 40%
Biochemistry, Genetics and Molecular Biology 16 24%
Computer Science 3 4%
Arts and Humanities 2 3%
Engineering 2 3%
Other 3 4%
Unknown 15 22%

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 18 March 2021.
All research outputs
#5,296,800
of 18,873,384 outputs
Outputs from BMC Biotechnology
#324
of 880 outputs
Outputs of similar age
#90,810
of 285,016 outputs
Outputs of similar age from BMC Biotechnology
#1
of 1 outputs
Altmetric has tracked 18,873,384 research outputs across all sources so far. This one has received more attention than most of these and is in the 70th percentile.
So far Altmetric has tracked 880 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.6. This one has gotten more attention than average, scoring higher than 61% 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 285,016 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 67% of its contemporaries.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them