Table 6.

Summary of networks for the study of host-pathogen interaction.

Networks	Experimental data	Mathematical and computational approaches	Objective
Regulatory	Genomics; Transcriptomics; Transcription Start Site (5′-RACE); Binding sites global regulators (ChIP-chip)	Boolean; network analysis	Dynamic of regulation of genes involved in virulence and pathogenicity
Metabolic	Genomics; transcriptomics; Metabolomics; Phenotype microarrays; C13 labeling	Constraint-based modeling; elementary flux mode analysis; pathway enrichment analysis; network analysis	Metabolic capabilities; genes related with virulence and pathogenicity
Protein-protein interaction	Y2H; PCA; BiFC; Protein arrays; Pull down; Phage display	Phylogenetic methods; dynamical networks; machine learning	Identification of hubs involved in virulence and pathogenicity; Determination of interaction between proteins related with signaling and regulatory cascades
Signaling and regulatory	Transcriptomics; Fusion assays (LacZ reporter); Adherence assay; Biofilm formation (fluorescence)	Boolean; network analysis	Impact of sensors in regulation of virulence and pathogenesis; Cell-to-cell signaling; biofilm synthesis;
Signaling, regulatory and metabolic	Genomics; metabolomics; transcriptomics	Constraint-based modeling; boolean model hierarchical layers; network analysis	Model regulatory and metabolic network of QS system

The networks reviewed in this work, the experimental data (mainly at the level of omics), the mathematical and computational approaches applied for every network, and the research objective for the networks studied are summarized.