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Reconstruction of a gene regulatory network of the induced systemic resistance defense response in Arabidopsis using boolean networks.

Tania TimmermannBernardo GonzálezGonzalo A Ruz
Published in: BMC bioinformatics (2020)
A computational intelligence approach was designed to reconstruct a GRN underlying the ISR defense response in plants using gene expression time-series data of A. thaliana colonized by P. phytofirmans PsJN and subsequently infected with P. syringae DC3000. Using differential evolution, 1000 GRNs from time-series data were successfully inferred. Through the study of the network dynamics of the selected GRN, it can be concluded that it is structurally robust since three mutations were necessary to completely disarm the Boolean trajectory that represents the biological data. The proposed method to reconstruct GRNs is general and can be used to infer other biologically relevant networks to formulate new biological hypotheses.
Keyphrases
  • gene expression
  • electronic health record
  • big data
  • dna methylation
  • dendritic cells
  • machine learning
  • drug induced
  • diabetic rats
  • immune response
  • artificial intelligence
  • deep learning