↓ Skip to main content

Opportunities and challenges in modeling human brain disorders in transgenic primates

Overview of attention for article published in Nature Neuroscience, August 2016
Altmetric Badge

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 (92nd percentile)
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

news
2 news outlets
twitter
16 X users

Citations

dimensions_citation
116 Dimensions

Readers on

mendeley
246 Mendeley
citeulike
3 CiteULike
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Opportunities and challenges in modeling human brain disorders in transgenic primates
Published in
Nature Neuroscience, August 2016
DOI 10.1038/nn.4362
Pubmed ID
Authors

Charles G Jennings, Rogier Landman, Yang Zhou, Jitendra Sharma, Julia Hyman, J Anthony Movshon, Zilong Qiu, Angela C Roberts, Anna Wang Roe, Xiaoqin Wang, Huihui Zhou, Liping Wang, Feng Zhang, Robert Desimone, Guoping Feng

Abstract

Molecular genetic tools have had a profound impact on neuroscience, but until recently their application has largely been confined to a few model species, most notably mouse, zebrafish, Drosophila melanogaster and Caenorhabditis elegans. With the development of new genome engineering technologies such as CRISPR, it is becoming increasingly feasible to apply these molecular tools in a wider range of species, including nonhuman primates. This will lead to many opportunities for brain research, but it will also pose challenges. Here we identify some of these opportunities and challenges in light of recent and foreseeable technological advances and offer some suggestions. Our main focus is on the creation of new primate disease models for understanding the pathological mechanisms of brain disorders and for developing new approaches to effective treatment. However, we also emphasize that primate genetic models have great potential to address many fundamental questions about brain function, providing an essential foundation for future progress in disease research.

X Demographics

X Demographics

The data shown below were collected from the profiles of 16 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 246 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 5 2%
Korea, Republic of 1 <1%
Hong Kong 1 <1%
France 1 <1%
Canada 1 <1%
India 1 <1%
Japan 1 <1%
China 1 <1%
Unknown 234 95%

Demographic breakdown

Readers by professional status Count As %
Researcher 60 24%
Student > Ph. D. Student 56 23%
Student > Bachelor 24 10%
Student > Master 21 9%
Student > Doctoral Student 17 7%
Other 34 14%
Unknown 34 14%
Readers by discipline Count As %
Neuroscience 82 33%
Agricultural and Biological Sciences 46 19%
Biochemistry, Genetics and Molecular Biology 23 9%
Medicine and Dentistry 18 7%
Computer Science 7 3%
Other 36 15%
Unknown 34 14%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 25. 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 24 January 2018.
All research outputs
#1,348,832
of 23,577,654 outputs
Outputs from Nature Neuroscience
#1,876
of 5,324 outputs
Outputs of similar age
#25,693
of 340,680 outputs
Outputs of similar age from Nature Neuroscience
#51
of 79 outputs
Altmetric has tracked 23,577,654 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 94th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 5,324 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 54.3. This one has gotten more attention than average, scoring higher than 64% 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 340,680 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 92% of its contemporaries.
We're also able to compare this research output to 79 others from the same source and published within six weeks on either side of this one. This one is in the 35th percentile – i.e., 35% of its contemporaries scored the same or lower than it.