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To better understand genome evolution and evolution of virulence characteristics in Listeria, we used a next generation sequencing approach to generate draft genomes for seven strains representing Listeria species or clades for which genome sequences were not available.
It was originally intended only to generate draft articles for Nupedia, with finished articles moved to the latter.
Of the three E-Pae strains, 2250 generated the highest quality sequence and this, along with that of I-Pae, was used to generate draft de novo genome assemblies as described in MATERIALS AND METHODS.
We used high-throughput sequencing (HTS) technologies to generate draft genome sequences of seven unrelated C. perfringens poultry NE isolates and one isolate from a healthy bird, and identified additional novel NE-associated genes by comparison with nine publicly available reference genomes.
The RAVEN Toolbox was used to generate draft models (manuscript under review).
This reaction set was used to generate draft GEMs for each non-KEGG organisms.
A total of 71,424 random sequence files corresponding to approximately 7.7 genome equivalents were assembled to generate draft sequences.
From the short overlapping sequence fragments obtained, it is possible to generate draft genome sequences using various algorithms developed for de novo sequence assembly [ 5- 7].
In this way, a researcher can rapidly generate draft metabolic network reconstructions based on genomic comparisons with one or more reference networks.
Typically, this is done either by mapping to a reference sequence or by de novo assembly to generate draft genomes comprising multiple contiguous sequences (contigs).
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com