Background Nonalcoholic steatohepatitis (NASH) is a severe form of nonalcoholic fatty liver disease (NAFLD).The molecular pathological mechanism of NASH is poorly understood.A general understanding of disease mechanism and drug action will come from various sources of data such as physiological, biochemical and genomic parameters.Network analysis is a valuable computational approach to integrate these data, extract meaningful information and intuitionally reflect the relationship.Methods The underlying datasets for constructing networks are derived from public biological databases including Liverbase, Gene Expression Omnibus, GenBank, DrugBank and KEGG databases.In order to merge networks and annotations from multiple sources, tools supporting data interchange formats such as PSI-MI are used to enable loose program integration.Networks visualization is done within Cytoscape.Speculations The complex diseases like NALFD can be better understood from the perspective of dysregulated modules than at the individual gene level.Network-based methods using a wealth of technologies already developed in graph theory offer a straightforward mechanism to assess the new observations and existing data together.Therefore it will provide valuable scientific insights for target selection and identification in the drug discovery.