↓ Skip to main content

Development of a construct-based risk assessment framework for genetic engineered crops

Overview of attention for article published in Transgenic Research, June 2016
Altmetric Badge

About this Attention Score

  • Average Attention Score compared to outputs of the same age
  • Above-average Attention Score compared to outputs of the same age and source (55th percentile)

Mentioned by

twitter
2 X users

Citations

dimensions_citation
12 Dimensions

Readers on

mendeley
33 Mendeley
Title
Development of a construct-based risk assessment framework for genetic engineered crops
Published in
Transgenic Research, June 2016
DOI 10.1007/s11248-016-9955-3
Pubmed ID
Authors

M. P. Beker, P. Boari, M. Burachik, V. Cuadrado, M. Junco, S. Lede, M. A. Lema, D. Lewi, A. Maggi, I. Meoniz, G. Noé, C. Roca, C. Robredo, C. Rubinstein, C. Vicien, A. Whelan

Abstract

Experience gained in the risk assessment (RA) of genetically engineered (GE) crops since their first experimental introductions in the early nineties, has increased the level of familiarity with these breeding methodologies and has motivated several agencies and expert groups worldwide to revisit the scientific criteria underlying the RA process. Along these lines, the need to engage in a scientific discussion for the case of GE crops transformed with similar constructs was recently identified in Argentina. In response to this need, the Argentine branch of the International Life Sciences Institute (ILSI Argentina) convened a tripartite working group to discuss a science-based evaluation approach for transformation events developed with genetic constructs which are identical or similar to those used in previously evaluated or approved GE crops. This discussion considered new transformation events within the same or different species and covered both environmental and food safety aspects. A construct similarity concept was defined, considering the biological function of the introduced genes. Factors like environmental and dietary exposure, familiarity with both the crop and the trait as well as the crop biology, were identified as key to inform a construct-based RA process.

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 33 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 33 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 8 24%
Student > Bachelor 5 15%
Student > Master 3 9%
Other 2 6%
Student > Ph. D. Student 2 6%
Other 4 12%
Unknown 9 27%
Readers by discipline Count As %
Agricultural and Biological Sciences 13 39%
Biochemistry, Genetics and Molecular Biology 5 15%
Medicine and Dentistry 2 6%
Nursing and Health Professions 1 3%
Unspecified 1 3%
Other 2 6%
Unknown 9 27%
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 19 September 2016.
All research outputs
#14,268,471
of 22,880,691 outputs
Outputs from Transgenic Research
#694
of 892 outputs
Outputs of similar age
#201,712
of 352,807 outputs
Outputs of similar age from Transgenic Research
#3
of 9 outputs
Altmetric has tracked 22,880,691 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 892 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.7. This one is in the 21st percentile – i.e., 21% 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 352,807 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 40th percentile – i.e., 40% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 9 others from the same source and published within six weeks on either side of this one. This one has scored higher than 6 of them.