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The old and new face of craniofacial research: How animal models inform human craniofacial genetic and clinical data

Overview of attention for article published in Developmental Biology, January 2016
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Article details
Title
The old and new face of craniofacial research: How animal models inform human craniofacial genetic and clinical data
Published in
Developmental Biology, January 2016
DOI 10.1016/j.ydbio.2016.01.017
Pubmed ID
Authors
Abstract

The craniofacial skeletal structures that comprise the human head develop from multiple tissues that converge to form the bones and cartilage of the face. Because of their complex development and morphogenesis, many human birth defects arise due to disruptions in these cellular populations. Thus, determining how these structures normally develop is vital if we are to gain a deeper understanding of craniofacial birth defects and devise treatment and prevention options. In this review, we will focus on how animal model systems have been used historically and in an ongoing context to enhance our understanding of human craniofacial development. We do this by first highlighting "animal to man" approaches: that is, how animal models are being utilized to understand fundamental mechanisms of craniofacial development. We discuss emerging technologies, including high throughput sequencing and genome editing, and new animal repository resources, and how their application can revolutionize the future of animal models in craniofacial research. Secondly, we highlight "man to animal" approaches, including the current use of animal models to test the function of candidate human disease variants. Specifically, we outline a common workflow deployed after discovery of a potentially disease causing variant based on a select set of recent examples in which human mutations are investigated in vivo using animal models. Collectively, these topics will provide a pipeline for the use of animal models in understanding human craniofacial development and disease for clinical geneticist and basic researchers alike.

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X Demographics

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

Geographical breakdown

Geographical breakdown
Country Count As %
United States 1 <1%
Colombia 1 <1%
China 1 <1%
Brazil 1 <1%
Unknown 125 97%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Student > Ph. D. Student 27 21%
Researcher 18 14%
Professor 10 8%
Student > Bachelor 8 6%
Student > Postgraduate 8 6%
Other 26 20%
Unknown 32 25%
Readers by discipline
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 31 24%
Agricultural and Biological Sciences 27 21%
Medicine and Dentistry 22 17%
Nursing and Health Professions 2 2%
Computer Science 2 2%
Other 10 8%
Unknown 35 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 01 March 2023.
All research outputs
#19,069,115
of 28,494,563 outputs
Outputs from Developmental Biology
#4,462
of 5,822 outputs
Outputs of similar age
#248,727
of 413,872 outputs
Outputs of similar age from Developmental Biology
#36
of 65 outputs
Altmetric has tracked 28,494,563 research outputs across all sources so far. This one is in the 31st percentile – i.e., 31% of other outputs scored the same or lower than it.
So far Altmetric has tracked 5,822 research outputs from this source. They receive a mean Attention Score of 4.7. 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 413,872 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 37th percentile – i.e., 37% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 65 others from the same source and published within six weeks on either side of this one. This one is in the 40th percentile – i.e., 40% of its contemporaries scored the same or lower than it.