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Genome editing and genetic engineering in livestock for advancing agricultural and biomedical applications

Overview of attention for article published in Mammalian Genome, July 2017
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#38 of 1,154)
  • High Attention Score compared to outputs of the same age (84th percentile)
  • High Attention Score compared to outputs of the same age and source (87th percentile)

Mentioned by

blogs
1 blog
twitter
5 X users
patent
1 patent

Citations

dimensions_citation
17 Dimensions

Readers on

mendeley
60 Mendeley
Title
Genome editing and genetic engineering in livestock for advancing agricultural and biomedical applications
Published in
Mammalian Genome, July 2017
DOI 10.1007/s00335-017-9709-4
Pubmed ID
Authors

Bhanu P. Telugu, Ki-Eun Park, Chi-Hun Park

Abstract

Genetic modification of livestock has a longstanding and successful history, starting with domestication several thousand years ago. Modern animal breeding strategies predominantly based on marker-assisted and genomic selection, artificial insemination, and embryo transfer have led to significant improvement in the performance of domestic animals, and are the basis for regular supply of high quality animal derived food. However, the current strategy of breeding animals over multiple generations to introduce novel traits is not realistic in responding to the unprecedented challenges such as changing climate, pandemic diseases, and feeding an anticipated 3 billion increase in global population in the next three decades. Consequently, sophisticated genetic modifications that allow for seamless introgression of novel alleles or traits and introduction of precise modifications without affecting the overall genetic merit of the animal are required for addressing these pressing challenges. The requirement for precise modifications is especially important in the context of modeling human diseases for the development of therapeutic interventions. The animal science community envisions the genome editors as essential tools in addressing these critical priorities in agriculture and biomedicine, and for advancing livestock genetic engineering for agriculture, biomedical as well as "dual purpose" applications.

X Demographics

X Demographics

The data shown below were collected from the profiles of 5 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 60 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 60 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 11 18%
Student > Master 9 15%
Student > Bachelor 8 13%
Student > Ph. D. Student 4 7%
Professor 3 5%
Other 6 10%
Unknown 19 32%
Readers by discipline Count As %
Agricultural and Biological Sciences 18 30%
Biochemistry, Genetics and Molecular Biology 8 13%
Immunology and Microbiology 3 5%
Social Sciences 3 5%
Engineering 3 5%
Other 4 7%
Unknown 21 35%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 13. 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 12 January 2023.
All research outputs
#2,762,199
of 25,152,132 outputs
Outputs from Mammalian Genome
#38
of 1,154 outputs
Outputs of similar age
#49,398
of 317,906 outputs
Outputs of similar age from Mammalian Genome
#3
of 16 outputs
Altmetric has tracked 25,152,132 research outputs across all sources so far. Compared to these this one has done well and is in the 89th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,154 research outputs from this source. They receive a mean Attention Score of 4.7. This one has done particularly well, scoring higher than 96% 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 317,906 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 16 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 87% of its contemporaries.