A comprehensive understanding of lipidomic networks is essential before models of cells in normal and pathological conditions can be developed. The LIPID MAPS project generates large amounts of data on lipid metabolites and genes to quantitatively study macrophage lipid networks under normal and diseased conditions. This exemplar catalog of mammalian lipids will be of immense value to the community. The primary objective of Core B will be to coordinate the data and knowledge from LIPID MAPS project and disseminate it to the larger research community. Achieving this objective involves continued development of complex multi-tier informatics and computational infrastructure, including databases, applications, and interfaces. In the second phase of LIPID MAPS, we will build infrastructure for the management of data arising from measurements of lipids in macrophages isolated from animal models. To facilitate analysis of the data by the Lipidomic Core laboratories, a biologist-friendly statistics workbench will be developed. The major focus of Core C is Bioinformatics and Systems Biology of Lipidomic networks. The specific objectives include statistical analysis of data to decipher regulation of lipids under normal and pathological conditions, reconstruction of lipidomic networks, development of mechanisms and hypotheses of lipid modules involved in pathology, and quantitative analysis of lipids in a context-specific manner. The approaches to be taken include use of statistical methods such as analysis of variance, statistical learning, and mathematical methods that model lipidomic networks. The new strategies will also include development of methods to analyze gene expression changes to identify coordinately regulated genes and pathways and the study of fluxes of lipids through metabolic networks. Modeling the influences of genetic and pharmacological perturbations will form another aspect of the proposed work. The LIPID MAPS web resource is the first of its kind and provides a comprehensive list of mammalian lipids along with quantitative metrics (standards) and context-specific cellular networks of lipids. The Bioinformatics and Data Coordination Core will develop databases, tools, and interfaces to facilitate public use of this valuable resource.
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