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Dataset Information

Gene regulatory network inference and analysis of multidrug-resistant Pseudomonas aeruginosa.


ABSTRACT:

Background

Healthcare-associated infections caused by bacteria such as Pseudomonas aeruginosa are a major public health problem worldwide. Gene regulatory networks (GRN) computationally represent interactions among regulatory genes and their targets. They are an important approach to help understand bacterial behaviour and to provide novel ways of overcoming scientific challenges, including the identification of potential therapeutic targets and the development of new drugs.

Objectives

The goal of this study was to reconstruct the multidrug-resistant (MDR) P. aeruginosa GRN and to analyse its topological properties.

Methods

The methodology used in this study was based on gene orthology inference using the reciprocal best hit method. We used the genome of P. aeruginosa

SUBMITTER: Medeiros Filho F 

PROVIDER: S-EPMC6684008 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature