title: Omics meet networks - using systems approaches to infer regulatory networks in plants.
abstract: Many genomic-scale datasets in plants have been generated over the last few years. This substantial achievement has led to impressive progress, including some of the most detailed molecular maps in any multicellular organism. Networks and pathways have been reconstructed using transcriptome, genome-wide transcription factor binding, proteome and metabolome data, and subsequently used to infer functional interactions among genes, proteins, and metabolites. However, more sophisticated systems biology approaches are needed to integrate different omics datasets. Ultimately, the integration of diverse and massive datasets into coherent models will improve our understanding of the molecular networks that underlie biological processes.
authors.affiliation: Duke University, Department of Biology and Center for Systems Biology, USA.
authors.forename: Miguel A
authors.initials: MA
authors.lastname: Moreno-Risueno
authors.forename: Wolfgang
authors.initials: W
authors.lastname: Busch
authors.forename: Philip N
authors.initials: PN
authors.lastname: Benfey
mesh_terms: D018506:Gene Expression Regulation, Plant; D053263:Gene Regulatory Networks / Q000235:genetics*; D023281:Genomics / Q000379:methods*; D010944:Plants / Q000235:genetics*; D049490:Systems Biology; D014157:Transcription Factors / Q000378:metabolism
chemical_list: D014157:Transcription Factors