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Model Organisms Facilitate Rare Disease Diagnosis and Therapeutic Research

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

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (96th percentile)
  • High Attention Score compared to outputs of the same age and source (96th percentile)

Mentioned by

blogs
1 blog
twitter
104 X users
patent
1 patent
facebook
3 Facebook pages
googleplus
1 Google+ user

Citations

dimensions_citation
168 Dimensions

Readers on

mendeley
285 Mendeley
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Title
Model Organisms Facilitate Rare Disease Diagnosis and Therapeutic Research
Published in
Genetics, August 2017
DOI 10.1534/genetics.117.203067
Pubmed ID
Authors

Michael F. Wangler, Shinya Yamamoto, Hsiao-Tuan Chao, Jennifer E. Posey, Monte Westerfield, John Postlethwait, Members of the Undiagnosed Diseases Network, Philip Hieter, Kym M. Boycott, Philippe M. Campeau, Hugo J. Bellen

Abstract

Efforts to identify the genetic underpinnings of rare undiagnosed diseases increasingly involve the use of next-generation sequencing and comparative genomic hybridization methods. These efforts are limited by a lack of knowledge regarding gene function, and an inability to predict the impact of genetic variation on the encoded protein function. Diagnostic challenges posed by undiagnosed diseases have solutions in model organism research, which provides a wealth of detailed biological information. Model organism geneticists are by necessity experts in particular genes, gene families, specific organs, and biological functions. Here, we review the current state of research into undiagnosed diseases, highlighting large efforts in North America and internationally, including the Undiagnosed Diseases Network (UDN) (Supplemental Material, File S1) and UDN International (UDNI), the Centers for Mendelian Genomics (CMG), and the Canadian Rare Diseases Models and Mechanisms Network (RDMM). We discuss how merging human genetics with model organism research guides experimental studies to solve these medical mysteries, gain new insights into disease pathogenesis, and uncover new therapeutic strategies.

X Demographics

X Demographics

The data shown below were collected from the profiles of 104 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 285 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 285 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 43 15%
Student > Bachelor 41 14%
Student > Ph. D. Student 39 14%
Student > Master 19 7%
Professor 19 7%
Other 47 16%
Unknown 77 27%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 89 31%
Agricultural and Biological Sciences 41 14%
Neuroscience 18 6%
Medicine and Dentistry 15 5%
Computer Science 6 2%
Other 28 10%
Unknown 88 31%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 74. 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 February 2023.
All research outputs
#586,416
of 25,750,437 outputs
Outputs from Genetics
#102
of 7,435 outputs
Outputs of similar age
#12,097
of 324,968 outputs
Outputs of similar age from Genetics
#4
of 119 outputs
Altmetric has tracked 25,750,437 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 97th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,435 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.6. This one has done particularly well, scoring higher than 98% 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 324,968 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 96% of its contemporaries.
We're also able to compare this research output to 119 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 96% of its contemporaries.