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
Geographical breakdown
Country | Count | As % |
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United States | 10 | 28% |
United Kingdom | 4 | 11% |
Germany | 2 | 6% |
Canada | 2 | 6% |
Australia | 2 | 6% |
France | 2 | 6% |
Netherlands | 1 | 3% |
Sweden | 1 | 3% |
Spain | 1 | 3% |
Other | 0 | 0% |
Unknown | 11 | 31% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 20 | 56% |
Scientists | 14 | 39% |
Science communicators (journalists, bloggers, editors) | 1 | 3% |
Practitioners (doctors, other healthcare professionals) | 1 | 3% |
Mendeley readers
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% |