title: Improved understanding of gene expression regulation using systems biology.
abstract: This article reviews the current state of systems biology approaches, including the experimental tools used to generate 'omic' data and computational frameworks to interpret this data. Through illustrative examples, systems biology approaches to understand gene expression and gene expression regulation are discussed. Some of the challenges facing this field and the future opportunities in the systems biology era are highlighted.
authors.affiliation: Cornell University, School of Chemical & Biomolecular Engineering, 120 Olin Hall, Ithaca, NY 14853, USA. RSK23@cornell.edu
authors.forename: Robert S
authors.initials: RS
authors.lastname: Kuczenski
authors.forename: Kunal
authors.initials: K
authors.lastname: Aggarwal
authors.forename: Kelvin H
authors.initials: KH
authors.lastname: Lee
mesh_terms: D000818:Animals; D005690:Galactose / Q000235:genetics / Q000378:metabolism; D005786:Gene Expression Regulation / Q000502:physiology*; D006801:Humans; D008954:Models, Biological; D009369:Neoplasms / Q000235:genetics / Q000378:metabolism; D012984:Software; D049490:Systems Biology / Q000379:methods*
chemical_list: D005690:Galactose