↓ Skip to main content

Zebrafish models in translational research: tipping the scales toward advancements in human health

Overview of attention for article published in Disease Models and Mechanisms, June 2014
Altmetric Badge

About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#16 of 1,922)
  • High Attention Score compared to outputs of the same age (98th percentile)
  • High Attention Score compared to outputs of the same age and source (94th percentile)

Mentioned by

news
7 news outlets
blogs
1 blog
policy
1 policy source
twitter
36 X users
facebook
3 Facebook pages

Citations

dimensions_citation
158 Dimensions

Readers on

mendeley
264 Mendeley
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
Zebrafish models in translational research: tipping the scales toward advancements in human health
Published in
Disease Models and Mechanisms, June 2014
DOI 10.1242/dmm.015545
Pubmed ID
Authors

Jennifer B. Phillips, Monte Westerfield

Abstract

Advances in genomics and next-generation sequencing have provided clinical researchers with unprecedented opportunities to understand the molecular basis of human genetic disorders. This abundance of information places new requirements on traditional disease models, which have the potential to be used to confirm newly identified pathogenic mutations and test the efficacy of emerging therapies. The unique attributes of zebrafish are being increasingly leveraged to create functional disease models, facilitate drug discovery, and provide critical scientific bases for the development of new clinical tools for the diagnosis and treatment of human disease. In this short review and the accompanying poster, we highlight a few illustrative examples of the applications of the zebrafish model to the study of human health and disease.

X Demographics

X Demographics

The data shown below were collected from the profiles of 36 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 264 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
India 2 <1%
United States 2 <1%
United Kingdom 1 <1%
Portugal 1 <1%
Spain 1 <1%
Poland 1 <1%
Unknown 256 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 55 21%
Student > Bachelor 37 14%
Researcher 32 12%
Student > Master 32 12%
Student > Doctoral Student 18 7%
Other 42 16%
Unknown 48 18%
Readers by discipline Count As %
Agricultural and Biological Sciences 78 30%
Biochemistry, Genetics and Molecular Biology 64 24%
Neuroscience 16 6%
Medicine and Dentistry 15 6%
Pharmacology, Toxicology and Pharmaceutical Science 7 3%
Other 25 9%
Unknown 59 22%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 86. 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 February 2023.
All research outputs
#494,370
of 25,374,647 outputs
Outputs from Disease Models and Mechanisms
#16
of 1,922 outputs
Outputs of similar age
#4,315
of 242,574 outputs
Outputs of similar age from Disease Models and Mechanisms
#1
of 19 outputs
Altmetric has tracked 25,374,647 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 98th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,922 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.4. This one has done particularly well, scoring higher than 99% 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 242,574 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 98% of its contemporaries.
We're also able to compare this research output to 19 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 94% of its contemporaries.