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Found 9 result(s)
The Allen Brain Atlas provides a unique online public resource integrating extensive gene expression data, connectivity data and neuroanatomical information with powerful search and viewing tools for the adult and developing brain in mouse, human and non-human primate
The IMEx consortium is an international collaboration between a group of major public interaction data providers who have agreed to share curation effort and develop and work to a single set of curation rules when capturing data from both directly deposited interaction data or from publications in peer-reviewed journals, capture full details of an interaction in a “deep” curation model, perform a complete curation of all protein-protein interactions experimentally demonstrated within a publication, make these interaction available in a single search interface on a common website, provide the data in standards compliant download formats, make all IMEx records freely accessible under the Creative Commons Attribution License
STRING is a database of known and predicted protein interactions. The interactions include direct (physical) and indirect (functional) associations; they are derived from four sources: - Genomic Context - High-throughput Experiments - (Conserved) Coexpression - Previous Knowledge STRING quantitatively integrates interaction data from these sources for a large number of organisms, and transfers information between these organisms where applicable.
mentha archives evidence collected from different sources and presents these data in a complete and comprehensive way. Its data comes from manually curated protein-protein interaction databases that have adhered to the IMEx consortium. The aggregated data forms an interactome which includes many organisms. mentha is a resource that offers a series of tools to analyse selected proteins in the context of a network of interactions. Protein interaction databases archive protein-protein interaction (PPI) information from published articles. However, no database alone has sufficient literature coverage to offer a complete resource to investigate "the interactome". mentha's approach generates every week a consistent interactome (graph). Most importantly, the procedure assigns to each interaction a reliability score that takes into account all the supporting evidence. mentha offers eight interactomes (Homo sapiens, Arabidopsis thaliana, Caenorhabditis elegans, Drosophila melanogaster, Escherichia coli K12, Mus musculus, Rattus norvegicus, Saccharomyces cerevisiae) plus a global network that comprises every organism, including those not mentioned. The website and the graphical application are designed to make the data stored in mentha accessible and analysable to all users. Source databases are: MINT, IntAct, DIP, MatrixDB and BioGRID.
MassBank of North America (MoNA) is a metadata-centric, auto-curating repository designed for efficient storage and querying of mass spectral records. It intends to serve as a the framework for a centralized, collaborative database of metabolite mass spectra, metadata and associated compounds. MoNA currently contains over 200,000 mass spectral records from experimental and in-silico libraries as well as from user contributions.
The Database explores the interactions of chemicals and proteins. It integrates information about interactions from metabolic pathways, crystal structures, binding experiments and drug-target relationships. Inferred information from phenotypic effects, text mining and chemical structure similarity is used to predict relations between chemicals. STITCH further allows exploring the network of chemical relations, also in the context of associated binding proteins.
Database of mass spectra of known, unknown and provisionally identified substances. MassBank is the first public repository of mass spectral data for sharing them among scientific research community. MassBank data are useful for the chemical identification and structure elucidation of chemical compounds detected by mass spectrometry.
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.
Tthe Lipidomics Gateway - a free, comprehensive website for researchers interested in lipid biology, provided by the LIPID MAPS (Lipid Metabolites and Pathways Strategy) Consortium. The LIPID MAPS Lipidomics Gateway provides a rich collection of information and resources to help you stay abreast of the latest developments in this rapidly expanding field. LIPID Metabolites And Pathways Strategy (LIPID MAPS®) is a multi-institutional effort created in 2003 to identify and quantitate, using a systems biology approach and sophisticated mass spectrometers, all of the major — and many minor — lipid species in mammalian cells, as well as to quantitate the changes in these species in response to perturbation. The ultimate goal of our research is to better understand lipid metabolism and the active role lipids play in diabetes, stroke, cancer, arthritis, Alzheimer's and other lipid-based diseases in order to facilitate development of more effective treatments. Since our inception, we have made great strides toward defining the "lipidome" (an inventory of the thousands of individual lipid molecular species) in the mouse macrophage. We have also worked to make lipid analysis easier and more accessible for the broader scientific community and to advance a robust research infrastructure for the international research community. We share new lipidomics findings and methods, hold annual meetings open to all interested investigators, and are exploring joint efforts to extend the use of these powerful new methods to new applications