The goal of the Common Fund’s Metabolomics program is to inform basic, translational, and clinical research. Metabolomics is the scientific study of the chemical reactions that occur in organisms, cells, or tissues. Each reaction produces small chemicals called metabolites, which play critical roles in keeping our cells healthy and functioning properly. As these different chemical reactions and the metabolites they produce are unique to every individual, by improving metabolomics methods and making them more accessible to different researchers it may allow for more personalized diagnosis of disease and treatment methods moving forward.
The Metabolomics Common Fund’s National Metabolomics Data Repository(NMDR), housed at the San Diego Supercomputer Center (SDSC), University of California, San Diego, has developed the Metabolomics Workbench. The Metabolomics Workbench serves as a national and international repository for metabolomics data and metadata and provides analysis tools and access to metabolite standards, protocols, tutorials, training, and more.
The data and other resources developed by the Common Fund Metabolomics program are managed by the Data
Repository and Coordinating Center (DRCC) at the San Diego Supercomputer Center, University of California, San
Diego. The DRCC makes these materials publicly available through the Metabolomics Workbench website.
The Omics Discovery Index (OmicsDI) provides a knowledge discovery framework across heterogeneous omics data (genomics, proteomics, transcriptomics and metabolomics).
Most data in the Datatsets Discovery Index can be accessed programmatically using a RESTful API. The API implementation is based on the Spring Rest Framework. Web-browsable API The OmicsDI API is web browsable, which means that: The query results returned by the API are available in JSONformat and also XML. This ensures that they can be viewed by human and accessed programmatically by computer. The main RESTful API page provides a simple web-based user interface, which allows developers to familiarize themselves with the API and get a better sense of the OmicsDI data before writing a single line of code.