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image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Computerarrow_drop_down
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
Computer
Article . 2002 . Peer-reviewed
License: IEEE Copyright
Data sources: Crossref
DBLP
Article . 2002
Data sources: DBLP
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Genome sequence assembly: algorithms and issues

Authors: Mihai Pop; Steven Salzberg; Martin Shumway;

Genome sequence assembly: algorithms and issues

Abstract

Ultimately, genome sequencing seeks to provide an organism's complete DNA sequence. Automation of DNA sequencing allowed scientists to decode entire genomes and gave birth to genomics, the analytic and comparative study of genomes. Although genomes can include billions of nucleotides, the chemical reactions researchers use to decode the DNA are accurate for only about 600 to 700 nucleotides at a time. The DNA reads that sequencing produces must then be assembled into a complete picture of the genome. Errors and certain DNA characteristics complicate assembly. Resolving these problems entails an additional and costly finishing phase that involves extensive human intervention. Assembly programs can dramatically reduce this cost by taking into account additional information obtained during finishing. The paper considers how algorithms that can assemble millions of DNA fragments into gene sequences underlie the current revolution in biotechnology, helping researchers build the growing database of complete genomes.

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    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 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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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!
50
Top 10%
Top 10%
Top 10%
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