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Peptidome was a public repository that archived tandem mass spectrometry peptide and protein identification data generated by the scientific community. This repository is now offline and is in archival mode. All data may be obtained from the Peptidome FTP site. Due to budgetary constraints NCBI has discontinued the Peptidome Repository. All existing data and metadata files will continue to be made available from our ftp server a ftp://ftp.ncbi.nih.gov/pub/peptidome/ indefinitely. Those files are named according to their Peptidome accession number, allowing cited data to be identified and downloaded. All of the Peptidome studies have been made publicly available at the PRoteomics IDEntifications (PRIDE) database. A map of Peptidome to Pride accessions may be found at ftp://ftp.ncbi.nih.gov/pub/peptidome/peptidome-pride_map.txt. If you have any specific questions, please feel free to contact us at info@ncbi.nlm.nih.gov.
The UniProt Knowledgebase (UniProtKB) is the central hub for the collection of functional information on proteins, with accurate, consistent and rich annotation. In addition to capturing the core data mandatory for each UniProtKB entry (mainly, the amino acid sequence, protein name or description, taxonomic data and citation information), as much annotation information as possible is added. This includes widely accepted biological ontologies, classifications and cross-references, and clear indications of the quality of annotation in the form of evidence attribution of experimental and computational data. The Universal Protein Resource (UniProt) is a comprehensive resource for protein sequence and annotation data. The UniProt databases are the UniProt Knowledgebase (UniProtKB), the UniProt Reference Clusters (UniRef), and the UniProt Archive (UniParc). The UniProt Metagenomic and Environmental Sequences (UniMES) database is a repository specifically developed for metagenomic and environmental data. The UniProt Knowledgebase,is an expertly and richly curated protein database, consisting of two sections called UniProtKB/Swiss-Prot and UniProtKB/TrEMBL.
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The Small Molecule Pathway Database (SMPDB) contains small molecule pathways found in humans, which are presented visually. All SMPDB pathways include information on the relevant organs, subcellular compartments, protein cofactors, protein locations, metabolite locations, chemical structures and protein quaternary structures. Accompanying data includes detailed descriptions and references, providing an overview of the pathway, condition or processes depicted in each diagram.
HumanCyc provides an encyclopedic reference on human metabolic pathways. It provides a zoomable human metabolic map diagram, and it has been used to generate a steady-state quantitative model of human metabolism. 2016: Subscriptions are now required to access HumanCyc. For more information on obtaining a subscription, click here: http://www.phoenixbioinformatics.org/biocyc#product-biocyc-subscription
GeneLab is an interactive, open-access resource where scientists can upload, download, store, search, share, transfer, and analyze omics data from spaceflight and corresponding analogue experiments. Users can explore GeneLab datasets in the Data Repository, analyze data using the Analysis Platform, and create collaborative projects using the Collaborative Workspace. GeneLab promises to facilitate and improve information sharing, foster innovation, and increase the pace of scientific discovery from extremely rare and valuable space biology experiments. Discoveries made using GeneLab have begun and will continue to deepen our understanding of biology, advance the field of genomics, and help to discover cures for diseases, create better diagnostic tools, and ultimately allow astronauts to better withstand the rigors of long-duration spaceflight. GeneLab helps scientists understand how the fundamental building blocks of life itself – DNA, RNA, proteins, and metabolites – change from exposure to microgravity, radiation, and other aspects of the space environment. GeneLab does so by providing fully coordinated epigenomics, genomics, transcriptomics, proteomics, and metabolomics data alongside essential metadata describing each spaceflight and space-relevant experiment. By carefully curating and implementing best practices for data standards, users can combine individual GeneLab datasets to gain new, comprehensive insights about the effects of spaceflight on biology. In this way, GeneLab extends the scientific knowledge gained from each biological experiment conducted in space, allowing scientists from around the world to make novel discoveries and develop new hypotheses from these priceless data.