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Trends in Biotechnology
Article . 2019 . Peer-reviewed
License: CC BY NC ND
Data sources: Crossref
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Trends in Biotechnology
Article
License: CC BY NC ND
Data sources: UnpayWall
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Newest Methods for Detecting Structural Variations

Authors: Wouter De Coster; Christine Van Broeckhoven;

Newest Methods for Detecting Structural Variations

Abstract

A substantial amount of structural variation in the human genome remains uninvestigated due to the limitations of existing technologies, the presence of repetitive sequences, and the complexity of a diploid genome. New technologies have been developed, increasing resolution and appreciation of structural variation and how it affects human diversity and disease. The genetic etiology of most patients with complex disorders such as neurodegenerative brain diseases is not yet elucidated, complicating disease diagnosis, genetic counseling, and understanding of underlying pathological mechanisms needed to develop therapeutic interventions. Here, we focus on innovative progress and opportunities provided by the newest methods such as linked read sequencing, strand-specific sequencing, and long-read sequencing. Finally, we describe a strategy for generating a comprehensive catalog of structural variations across populations.

Country
Belgium
Related Organizations
Keywords

Base Sequence, Genome, Human, Genetic Variation, High-Throughput Nucleotide Sequencing, Humans, Sequence Analysis, DNA, Biology, Engineering sciences. Technology

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    selected citations
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    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    88
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 1%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 1%
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
88
Top 1%
Top 10%
Top 1%
Green
hybrid