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Evolutionary Bioinformatics
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PubMed Central
Article . 2013
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Evolutionary Bioinformatics
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Evolutionary Bioinformatics
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EDGE-pro: Estimated Degree of Gene Expression in Prokaryotic Genomes

Authors: Tanja Magoc; Derrick Wood; Steven L. Salzberg';

EDGE-pro: Estimated Degree of Gene Expression in Prokaryotic Genomes

Abstract

Background The expression levels of bacterial genes can be measured directly using next-generation sequencing (NGS) methods, offering much greater sensitivity and accuracy than earlier, microarray-based methods. Most bioinformatics software for estimating levels of gene expression from NGS data has been designed for eukaryotic genomes, with algorithms focusing particularly on detection of splicing patterns. These methods do not perform well on bacterial genomes. Results Here we describe the first software system designed explicitly for quantifying the degree of gene expression in bacteria and other prokaryotes. EDGE-pro (Estimated Degree of Gene Expression in PROkaryotes) processes the raw data from an RNA-seq experiment on a bacterial or archaeal species and produces estimates of the expression levels for each gene in these gene-dense genomes. Software The EDGE-pro tool is implemented as a pipeline of C++ and Perl programs and is freely available as open-source code at http://www.genomics.jhu.edu/software/EDGE/index.shtml .

Keywords

Technical Advance, Evolution, QH359-425

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    influence
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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!
109
Top 10%
Top 10%
Top 10%
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gold