Metabolic models of metabolism are mathematical, network-based, and large-scale representations of the set of chemical reactions for which various types of evidence exists. These models are generally reconstructed from publicly available data, or in collaboration with in vivo researchers, and their reconstruction and analysis is often accomplished using freely available programming languages and packages, or programmable computational methods. Many such models account for all reactions supported by their annotated genome, in which case they are said to be genome-scale models (GSM). GSMs span many levels of complexity ranging from purely stoichiometric to metabolic networks accounting for protein synthesis (resource analysis models) to kinetic models of metabolism. Metabolic models have been applied to a wide range of applications including bioengineering (their most typical application), investigation of metabolism, and medical applications. Examples of metabolic investigation include resolution of basic metabolic questions such as atypical energy sources, metabolic reprogramming under stress, exploring understudied pathways, multi-scale elucidation of regulation, and drug repurposing. My proposed research plan leverages the breadth of systems that can be modeled, model types, model applications, the development of new modeling techniques, and publicly available yet underleveraged datasets, along with potential collaborations within WSU and the PNNL to develop a broad program of research addressing key challenges including improved plant tolerance to heat and drought stresses, drug repurposing, and designing cyanobacteria as CO2 to biochemical platforms. These proposed applications highlight only a fraction of the breadth of modeling applications, and our lab is actively searching for collaborative in vivo and in vitro researchers with which to work to use modeling techniques to answer fundamental research questions.