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Personalised Medicine

Overview of attention for book
Attention for Chapter 10: The Power of Zebrafish in Personalised Medicine
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  • Good Attention Score compared to outputs of the same age and source (73rd percentile)

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Chapter title
The Power of Zebrafish in Personalised Medicine
Chapter number 10
Book title
Personalised Medicine
Published in
Advances in experimental medicine and biology, August 2017
DOI 10.1007/978-3-319-60733-7_10
Pubmed ID
Book ISBNs
978-3-31-960731-3, 978-3-31-960733-7
Authors

Baxendale, Sarah, van Eeden, Freek, Wilkinson, Robert, Sarah Baxendale, Freek van Eeden, Robert Wilkinson

Abstract

The goal of personalised medicine is to develop tailor-made therapies for patients in whom currently available therapeutics fail. This approach requires correlating individual patient genotype data to specific disease phenotype data and using these stratified data sets to identify bespoke therapeutics. Applications for personalised medicine include common complex diseases which may have multiple targets, as well as rare monogenic disorders, for which the target may be unknown. In both cases, whole genome sequence analysis (WGS) is discovering large numbers of disease associated mutations in new candidate genes and potential modifier genes. Currently, the main limiting factor is the determination of which mutated genes are important for disease progression and therefore represent potential targets for drug discovery. Zebrafish have gained popularity as a model organism for understanding developmental processes, disease mechanisms and more recently for drug discovery and toxicity testing. In this chapter, we will examine the diverse roles that zebrafish can make in the expanding field of personalised medicine, from generating humanised disease models to xenograft screening of different cancer cell lines, through to finding new drugs via in vivo phenotypic screens. We will discuss the tools available for zebrafish research and recent advances in techniques, highlighting the advantages and potential of using zebrafish for high throughput disease modeling and precision drug discovery.

X Demographics

X Demographics

The data shown below were collected from the profiles of 3 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 69 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 69 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 11 16%
Student > Ph. D. Student 11 16%
Student > Bachelor 10 14%
Student > Master 9 13%
Student > Doctoral Student 4 6%
Other 6 9%
Unknown 18 26%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 16 23%
Agricultural and Biological Sciences 11 16%
Medicine and Dentistry 7 10%
Neuroscience 5 7%
Pharmacology, Toxicology and Pharmaceutical Science 1 1%
Other 5 7%
Unknown 24 35%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 25 February 2023.
All research outputs
#13,585,641
of 23,427,600 outputs
Outputs from Advances in experimental medicine and biology
#1,864
of 5,025 outputs
Outputs of similar age
#156,516
of 317,455 outputs
Outputs of similar age from Advances in experimental medicine and biology
#5
of 19 outputs
Altmetric has tracked 23,427,600 research outputs across all sources so far. This one is in the 41st percentile – i.e., 41% of other outputs scored the same or lower than it.
So far Altmetric has tracked 5,025 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.3. This one has gotten more attention than average, scoring higher than 61% 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 317,455 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 49th percentile – i.e., 49% of its contemporaries scored the same or lower than it.
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 gotten more attention than average, scoring higher than 73% of its contemporaries.