The objective of this proposal, Metabolomics Data Center and Workbench (MDCW), is the creation of a scalable and extensible informatics infrastructure which will serve as a national metabolomics resource. This is a companion proposal to RCMRCs and is a part of the Common Fund Initiative in metabolomics. The proposed MDCW will coordinate data activities of national and international metabolomics centers and initiatives, serve as a national data repository and develop a Workbench that will have data, query and analysis interfaces, and tools for interactive analysis and integration of metabolomics data. The proposed work will build on the extant infrastructure for lipids developed by the PI's laboratory as a part of the NIH Glue Grant initiative on Lipidomics. The specific objectives of this proposal are, a) development of a metabolomics data repository, tools and interfaces, b) develop a cloud computing infrastructure for metabolomics, c) coordinate RCMRCs and other metabolomics initiatives and d) provide the resources for advancing metabolomics education and research to enable new biomedicine.
The major aim of this proposal is the development of a community-driven data repository for metabolomics. More specifically, the proposed Center will coordinate informatics efforts of RCMRCs and present all data from the Cores and other metabolomics efforts to the biomedical research community. In addition, the proposal will build a computational infrastructure that will be appropriate for metabolomics research. Most importantly, the Center will provide the enabling informatics infrastructure for next generation biomedical research involving metabolomics.
|Mach, Núria; Ramayo-Caldas, Yuliaxis; Clark, Allison et al. (2017) Understanding the response to endurance exercise using a systems biology approach: combining blood metabolomics, transcriptomics and miRNomics in horses. BMC Genomics 18:187|
|Thonusin, Chanisa; IglayReger, Heidi B; Soni, Tanu et al. (2017) Evaluation of intensity drift correction strategies using MetaboDrift, a normalization tool for multi-batch metabolomics data. J Chromatogr A 1523:265-274|
|Perez-Riverol, Yasset; Bai, Mingze; da Veiga Leprevost, Felipe et al. (2017) Discovering and linking public omics data sets using the Omics Discovery Index. Nat Biotechnol 35:406-409|
|Gupta, Shakti; Kihara, Yasuyuki; Maurya, Mano R et al. (2016) Computational Modeling of Competitive Metabolism between ?3- and ?6-Polyunsaturated Fatty Acids in Inflammatory Macrophages. J Phys Chem B 120:8346-53|
|Min, Jun S; DeAngelis, Robert A; Reis, Edimara S et al. (2016) Systems Analysis of the Complement-Induced Priming Phase of Liver Regeneration. J Immunol 197:2500-8|
|Sud, Manish; Fahy, Eoin; Cotter, Dawn et al. (2016) Metabolomics Workbench: An international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools. Nucleic Acids Res 44:D463-70|
|Clendinen, Chaevien S; Pasquel, Christian; Ajredini, Ramadan et al. (2015) (13)C NMR Metabolomics: INADEQUATE Network Analysis. Anal Chem 87:5698-706|