Reverse Engineering Gene Regulatory Networks Related to Quorum Sensing in the Plant Pathogen Pectobacterium atrosepticum

摘要: The objective of the project reported in present chapter was reverse engineering gene regulatory networks related to quorum sensing plant pathogen Pectobacterium atrosepticum from micorarray expression profiles, obtained wild-type and eight knockout strains. To this end, we have applied various recent methods multivariate statistics machine learning: graphical Gaussian models, sparse Bayesian regression, LASSO (least absolute shrinkage selection operator), networks, nested effects models. We investigated degree similarity between predictions with different approaches, assessed consistency reconstructed terms global topological network properties, based on node distribution. concludes a biological evaluation predicted structures.