A Boolean network model of bacterial quorumsensing systems

Gonzalo A. Ruz, Ana Zúñiga, Eric Goles

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

There are several mathematical models to represent gene regulatory networks, one of the simplest is the Boolean network paradigm. In this paper, we reconstruct a regulatory network of bacterial quorum-sensing systems, in particular, we consider Paraburkholderia phytofirmans PsJN which is a plant growth promoting bacteria that produces positive effects in horticultural crops like tomato, potato and grape. To learn the regulatory network from temporal expression pattern of quorum-sensing genes at root plants, we present a methodology that considers the training of perceptrons for each gene and then the integration into one Boolean regulatory network. Using the proposed approach, we were able to infer a regulatory network model whose topology and dynamic exhibited was helpful to gain insight on the quorum-sensing systems regulation mechanism. We compared our results with REVEAL and Best-Fit extension algorithm, showing that the proposed neural network approach obtained a more biologically meaningful network and dynamics, demonstrating the effectiveness of the proposed method.

Original languageEnglish
Pages (from-to)123-144
Number of pages22
JournalInternational Journal of Data Mining and Bioinformatics
Volume21
Issue number2
DOIs
StatePublished - 2018

Keywords

  • Boolean networks
  • Gene regulatory networks
  • Network inference
  • Neural networks
  • Quorum-sensing systems

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