title: REGNET: mining context-specific human transcription networks using composite genomic information.
abstract: BACKGROUND
  Genome-wide expression profiles reflect the transcriptional networks specific to the given cell context. However, most statistical models try to estimate the average connectivity of the networks from a collection of gene expression data, and are unable to characterize the context-specific transcriptional regulations. We propose an approach for mining context-specific transcription networks from a large collection of gene expression fold-change profiles and composite gene-set information.
  
  
  RESULTS
  Using a composite gene-set analysis method, we combine the information of transcription factor binding sites, Gene Ontology or pathway gene sets and gene expression fold-change profiles for a variety of cell conditions. We then collected all the significant patterns and constructed a database of context-specific transcription networks for human (REGNET). As a result, context-specific roles of transcription factors as well as their functional targets are readily explored. To validate the approach, nine predicted targets of E2F1 in HeLa cells were tested using chromatin immunoprecipitation assay. Among them, five (Gadd45b, Dusp6, Mll5, Bmp2 and E2f3) were successfully bound by E2F1. c-JUN and the EMT transcription networks were also validated from literature.
  
  
  CONCLUSIONS
  REGNET is a useful tool for exploring the ternary relationships among the transcription factors, their functional targets and the corresponding cell conditions. It is able to provide useful clues for novel cell-specific transcriptional regulations. The REGNET database is available at http://mgrc.kribb.re.kr/regnet.
authors.forename: Sang-Mun
authors.initials: SM
authors.lastname: Chi
authors.forename: Young-Kyo
authors.initials: YK
authors.lastname: Seo
authors.forename: Young-Kyu
authors.initials: YK
authors.lastname: Park
authors.forename: Sora
authors.initials: S
authors.lastname: Yoon
authors.forename: Chan Young
authors.initials: CY
authors.lastname: Park
authors.forename: Yong Sung
authors.initials: YS
authors.lastname: Kim
authors.affiliation: School of Life Sciences, UNIST, Ulsan, Republic of Korea. kimsy@kribb.re.kr.
authors.forename: Seon-Young
authors.initials: SY
authors.lastname: Kim
authors.forename: Dougu
authors.initials: D
authors.lastname: Nam
mesh_terms: D001665:Binding Sites; D019295:Computational Biology / Q000379:methods*; D030541:Databases, Genetic; D015870:Gene Expression; D063990:Gene Ontology; D053263:Gene Regulatory Networks; D015894:Genome, Human; D006367:HeLa Cells; D006801:Humans; D015203:Reproducibility of Results; D012984:Software; D014157:Transcription Factors / Q000378:metabolism*
chemical_list: D014157:Transcription Factors