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Starting September 2013, MINT uses the IntAct database infrastructure to limit the duplication of efforts and to optimise future software development. Data manually curated by the MINT curators can now be accessed from the IntAct homepage at the EBI. Data maintenance and release, MINT PSICQUIC and IMEx services are under the responsibility of the IntAct team, while curation effort will be carried by both groups. The MINT development team now focuses on two new developments: mentha that integrates protein interaction information curated by IMEx databases and SIGNOR a database of logic relationships between human proteins. MINT is a public repository for molecular interactions reported in peer-reviewed journals.IT is a collection of molecular interaction databases that can be used to search for, analyze and graphically display molecular interaction networks and pathways from a wide variety of species. MINT is comprised of separate database components. HomoMINT, is an inferred human protein interatction database. Domino, is database of domain peptide interactions. A new component has been added called VirusMINT that explores the interactions of viral proteins with human proteins.
With the creation of the Metabolomics Data Repository managed by Data Repository and Coordination Center (DRCC), the NIH acknowledges the importance of data sharing for metabolomics. Metabolomics represents the systematic study of low molecular weight molecules found in a biological sample, providing a "snapshot" of the current and actual state of the cell or organism at a specific point in time. Thus, the metabolome represents the functional activity of biological systems. As with other ‘omics’, metabolites are conserved across animals, plants and microbial species, facilitating the extrapolation of research findings in laboratory animals to humans. Common technologies for measuring the metabolome include mass spectrometry (MS) and nuclear magnetic resonance spectroscopy (NMR), which can measure hundreds to thousands of unique chemical entities. Data sharing in metabolomics will include primary raw data and the biological and analytical meta-data necessary to interpret these data. Through cooperation between investigators, metabolomics laboratories and data coordinating centers, these data sets should provide a rich resource for the research community to enhance preclinical, clinical and translational research.