The integration of data across omics levels is necessary to accurately reflect physiology, whose behavior is not limited to one molecular component level. Further, integration of information across experimental platforms, time scales, dosing regiments, tissues, and organisms is necessary for the extraction of all possible meaning from the wealth of existing data stored across databases globally and for the development of research that is translatable between organisms. In the enclosed

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... enclosed dissertation, we present a pathway-based meta-analysis approach integrated with multivariate decomposition techniques for processing temporal expression data. This framework is designed for application to expression data from any omics level, incorporates information from multiple databases, and is modular in that it can interrogate expression data with pathways extracted from multiple databases. This framework is applied to investigate the dosing- and tissue-dependent effects of the corticosteroid methylprednisolone, as well as the endogenous expression of model organisms critical to pre-clinical studies, rat and mouse. Such analyses both characterize systems not yet completely understood and exemplify the strength of a systems pharmacology understanding applied within translational research.