title: Omics data input for metabolic modeling.
abstract: Recent advancements in high-throughput large-scale analytical methods to sequence genomes of organisms, and to quantify gene expression, proteins, lipids and metabolites have changed the paradigm of metabolic modeling. The cost of data generation and analysis has decreased significantly, which has allowed exponential increase in the amount of omics data being generated for an organism in a very short time. Compared to progress made in microbial metabolic modeling, plant metabolic modeling still remains limited due to its complex genomes and compartmentalization of metabolic reactions. Herein, we review and discuss different omics-datasets with potential application in the functional genomics. In particular, this review focuses on the application of omics-datasets towards construction and reconstruction of plant metabolic models.
authors.affiliation: Graduate School of Pharmaceutical Sciences, Chiba University, 1-8-1 Inohana, Chuo-ku, Chiba 260-8675, Japan. Electronic address: amit.rai@chiba-u.jp.
authors.forename: Amit
authors.initials: A
authors.lastname: Rai
authors.affiliation: Graduate School of Pharmaceutical Sciences, Chiba University, 1-8-1 Inohana, Chuo-ku, Chiba 260-8675, Japan; RIKEN Center for Sustainable Resource Science, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama 230-0045, Japan. Electronic address: kuzaki.saito@riken.jp.
authors.forename: Kazuki
authors.initials: K
authors.lastname: Saito
mesh_terms: D023281:Genomics / Q000379:methods; D006801:Humans; D050356:Lipid Metabolism; D055432:Metabolomics / Q000379:methods; D008954:Models, Biological; D010944:Plants / Q000378:metabolism