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<<<!!!<<< Effective May 2024, NCBI's Assembly resource will no longer be available. NCBI Assembly data can now be found on the NCBI Datasets genome pages. https://www.re3data.org/repository/r3d100014298 >>>!!!>>> A database providing information on the structure of assembled genomes, assembly names and other meta-data, statistical reports, and links to genomic sequence data.
NCBI Datasets is a continually evolving platform designed to provide easy and intuitive access to NCBI’s sequence data and metadata. NCBI Datasets is part of the NIH Comparative Genomics Resource (CGR). CGR facilitates reliable comparative genomics analyses for all eukaryotic organisms through an NCBI Toolkit and community collaboration.
The PeptideAtlas validates expressed proteins to provide eukaryotic genome data. Peptide Atlas provides data to advance biological discoveries in humans. The PeptideAtlas accepts proteomic data from high-throughput processes and encourages data submission.
MatrixDB is a freely available database focused on interactions established by extracellular proteins and polysaccharides. MatrixDB takes into account the multimetric nature of the extracellular proteins (e.g. collagens, laminins and thrombospondins are multimers). MatrixDB includes interaction data extracted from the literature by manual curation in our lab, and offers access to relevant data involving extracellular proteins provided by our IMEx partner databases through the PSICQUIC webservice, as well as data from the Human Protein Reference Database. MatrixDB is in charge of the curation of papers published in Matrix Biology since January 2009
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The Human Metabolome Database (HMDB) is a freely available electronic database containing detailed information about small molecule metabolites found in the human body. It is intended to be used for applications in metabolomics, clinical chemistry, biomarker discovery and general education.
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.