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Translational Informatics in Smart Healthcare

Overview of attention for book
Attention for Chapter 3: Newborn Screening in the Era of Precision Medicine
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Chapter title
Newborn Screening in the Era of Precision Medicine
Chapter number 3
Book title
Translational Informatics in Smart Healthcare
Published in
Advances in experimental medicine and biology, January 2017
DOI 10.1007/978-981-10-5717-5_3
Pubmed ID
Book ISBNs
978-9-81-105716-8, 978-9-81-105717-5
Authors

Lan Yang, Jiajia Chen, Bairong Shen

Abstract

As newborn screening success stories gained general confirmation during the past 50 years, scientists quickly discovered diagnostic tests for a host of genetic disorders that could be treated at birth. Outstanding progress in sequencing technologies over the last two decades has made it possible to comprehensively profile newborn screening (NBS) and identify clinically relevant genomic alterations. With the rapid developments in whole-genome sequencing (WGS) and whole-exome sequencing (WES) recently, we can detect newborns at the genomic level and be able to direct the appropriate diagnosis to the different individuals at the appropriate time, which is also encompassed in the concept of precision medicine. Besides, we can develop novel interventions directed at the molecular characteristics of genetic diseases in newborns. The implementation of genomics in NBS programs would provide an effective premise for the identification of the majority of genetic aberrations and primarily help in accurate guidance in treatment and better prediction. However, there are some debate correlated with the widespread application of genome sequencing in NBS due to some major concerns such as clinical analysis, result interpretation, storage of sequencing data, and communication of clinically relevant mutations to pediatricians and parents, along with the ethical, legal, and social implications (so-called ELSI). This review is focused on these critical issues and concerns about the expanding role of genomics in NBS for precision medicine. If WGS or WES is to be incorporated into NBS practice, considerations about these challenges should be carefully regarded and tackled properly to adapt the requirement of genome sequencing in the era of precision medicine.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 33 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 33 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 5 15%
Student > Master 5 15%
Student > Doctoral Student 2 6%
Other 2 6%
Researcher 2 6%
Other 5 15%
Unknown 12 36%
Readers by discipline Count As %
Medicine and Dentistry 11 33%
Biochemistry, Genetics and Molecular Biology 3 9%
Computer Science 3 9%
Pharmacology, Toxicology and Pharmaceutical Science 1 3%
Agricultural and Biological Sciences 1 3%
Other 2 6%
Unknown 12 36%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 17 September 2017.
All research outputs
#18,572,036
of 23,002,898 outputs
Outputs from Advances in experimental medicine and biology
#3,325
of 4,961 outputs
Outputs of similar age
#311,389
of 421,223 outputs
Outputs of similar age from Advances in experimental medicine and biology
#333
of 490 outputs
Altmetric has tracked 23,002,898 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 4,961 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.1. This one is in the 19th percentile – i.e., 19% 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 421,223 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 15th percentile – i.e., 15% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 490 others from the same source and published within six weeks on either side of this one. This one is in the 15th percentile – i.e., 15% of its contemporaries scored the same or lower than it.