IdentiCS — Identification of coding sequence and
in silico reconstruction of the metabolic network directly from unannotated
low-coverage bacterial genome sequence
Yi-Feng Chang (張益峰)
Abstract
Studying metabolic
network of an organism is able to understanding its physiology and phenotypic
behavior. The functionality of the potential metabolic network of a given
organism can also be experimentally studied by system perturbations at
physiological and genetic levels.
Usually, metabolic
network reconstruction of a new organism required its well-annotated genome
sequence. However, the process of annotating a new sequenced genome always time
consuming. Therefore, in this work, authors proposed a different but simple
approach to reduce the requirement of genome coverage.
First remove the
gene finding procedure from conventional metabolic network reconstruction
process. Then all of the available public annotated genome sequences are becoming
the query sequences; and the low genome coverage sequence is becoming a target
database. The reversed step of above mention, successfully reduce the genome
coverage requirement from 8 fold to 3.9 fold and also improved the coding
sequences recognition rate.
From: BMC
Bioinformatics Vol. 5, 2004.
References
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Ahren, D.G. and Ouzounis