In renal IRI, a recent study by Liu et. al. examined the Azathioprine changes of metabolites in a rat model using high-performance liquid chromatography coupled with mass spectrometry-based approach. While the study by Liu et al. revealed interesting changes, how the changes are related to kidney injury was not fully analyzed. It is also unclear if there are significant metabolic changes during the kidney recovery or repair phase following renal IRI. In addition, the differential changes in the metabolme of plasma, kidney cortex, and medulla are unknown. In this study, we analyzed the changes of metabolic profiles in kidney cortex, medulla, and serum after renal IRI in mice. The analysis covered the phases of initial kidney injury, peak injury, and the recovery. In addition to the overall change of metabolome, we also identified specific metabolites that showed early responses to ischemic injury and the perturbed metabolism pathways that are related to energy metabolism, osmotic regulation and the induction of inflammation. The informatics system used for sample management, data extraction and analysis consisted of four major components, the Laboratory Information Management System, the data extraction and peak-identification software, the data processing tools for quality control and compound identification, and a collection of information interpretation and visualization tools for use by data analysts. The Edrophonium chloride hardware and software foundations for these informatics components were the LAN backbone, and a database server running Oracle 10.2.0.1 Enterprise Edition. The data extraction of the raw mass spec data files yielded information that could loaded into a relational database and manipulated without resorting to BLOB manipulation. Once in the database the information was examined and the appropriate quality control limits were imposed. The peaks were identified using Metabolon��s proprietary peak integration software, and the component parts were stored in a separate and specifically designed complex data structure. The compounds were identified by comparison to library entries of purified standards or recurrent unknown entities.