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Found 46 result(s)
The PRIDE PRoteomics IDEntifications database is a centralized, standards compliant, public data repository for proteomics data, including protein and peptide identifications, post-translational modifications and supporting spectral evidence. PRIDE encourages and welcomes direct user submissions of mass spectrometry data to be published in peer-reviewed publications.
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ProteomicsDB started as a protein-centric in-memory database for the exploration of large collections of quantitative mass spectrometry-based proteomics data. The data types and contents grew over time to include RNA-Seq expression data, drug-target interactions and cell line viability data.
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MaxQB stores and displays collections of large proteomics projects and allows joint analysis and comparison. As a first dataset is contains proteome data of 11 different human cell lines. The 11 cell line proteomes together identify proteins expressed from more than half of all human genes. For each protein of interest, expression levels estimated by label-free quantification can be visualized across the cell lines. Similarly, the expression rank order and estimated amount of each protein within each proteome are plotted.
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NODE (The National Omics Data Encyclopedia) provides an integrated, compatible, comparable, and scalable multi-omics resource platform that supports flexible data management and effective data release. NODE uses a hierarchical data architecture to support storage of muti-omics data including sequencing data, MS based proteomics data, MS or NMR based metabolomics data, and fluorescence imaging data. Launched in early 2017, NODE has collected and published over 900 terabytes of omics data for researchers from China and all over the world in last three years, 22% of which contains multiple omics data. NODE provides functions around the whole life cycle of omics data, from data archive, data requests/responses to data sharing, data analysis, data review and publish.
FungiDB belongs to the EuPathDB family of databases and is an integrated genomic and functional genomic database for the kingdom Fungi. FungiDB was first released in early 2011 as a collaborative project between EuPathDB and the group of Jason Stajich (University of California, Riverside). At the end of 2015, FungiDB was integrated into the EuPathDB bioinformatic resource center. FungiDB integrates whole genome sequence and annotation and also includes experimental and environmental isolate sequence data. The database includes comparative genomics, analysis of gene expression, and supplemental bioinformatics analyses and a web interface for data-mining.
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.
<<<!!!<<<This is an archive of the old NEBC site from nebc.nerc.ac.uk and is no longer updated. For new information regarding NERC Environmental Omics and the Bio-Linux system please see the EOS site at http://environmentalomics.org. >>>!!!>>> Ongoing NEBC activities, including the development of Bio-Linux, are being moved into the new EOS programme http://environmentalomics.org/portfolio/big-data-infrastructure/ . Once the current material from this website has been moved into EOS, this NEBC site will remain on-line as an archive. EnvBase is the searchable index to the data deposited through the NEBC, as well as related NERC experimental data. At present this is chiefly from the grants funded by the NERC Environmental Genomics Science Programme and the subsequent Post-genomics and Proteomics Science Programme, but more data from ongoing projects continues to be added
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MyTardis began at Monash University to solve the problem of users needing to store large datasets and share them with collaborators online. Its particular focus is on integration with scientific instruments, instrument facilities and research lab file storage. Our belief is that the less effort a researcher has to expend safely storing data, the more likely they are to do so. This approach has flourished with MyTardis capturing data from areas such as protein crystallography, electron microscopy, medical imaging and proteomics and with deployments at Australian institutions such as University of Queensland, RMIT, University of Sydney and the Australian Synchrotron. Data access via https://www.massive.org.au/ and https://store.erc.monash.edu.au/experiment/view/104/ and see 'remarks'.
The DIP database catalogs experimentally determined interactions between proteins. It combines information from a variety of sources to create a single, consistent set of protein-protein interactions. The data stored within the DIP database were curated, both, manually by expert curators and also automatically using computational approaches that utilize the the knowledge about the protein-protein interaction networks extracted from the most reliable, core subset of the DIP data. Please, check the reference page to find articles describing the DIP database in greater detail. The Database of Ligand-Receptor Partners (DLRP) is a subset of DIP (Database of Interacting Proteins). The DLRP is a database of protein ligand and protein receptor pairs that are known to interact with each other. By interact we mean that the ligand and receptor are members of a ligand-receptor complex and, unless otherwise noted, transduce a signal. In some instances the ligand and/or receptor may form a heterocomplex with other ligands/receptors in order to be functional. We have entered the majority of interactions in DLRP as full DIP entries, with links to references and additional information
Swiss Institute of Bioinformatics (SIB) coordinates research and education in bioinformatics throughout Switzerland and provides bioinformatics services to the national and international research community. ExPASy gives access to numerous repositories and databases of SIB. For example: array map, MetaNetX, SWISS-MODEL and World-2DPAGE, and many others see a list here http://www.expasy.org/resources
Pathway Commons is a convenient point of access to biological pathway information collected from public pathway databases. Information is sourced from public pathway databases and is readily searched, visualized, and downloaded. The data is freely available under the license terms of each contributing database.
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
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BioSamples stores and supplies descriptions and metadata about biological samples used in research and development by academia and industry. Samples are either 'reference' samples (e.g. from 1000 Genomes, HipSci, FAANG) or have been used in an assay database such as the European Nucleotide Archive (ENA) or ArrayExpress.
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The Swedish Human Protein Atlas project has been set up to allow for a systematic exploration of the human proteome using Antibody-Based Proteomics. This is accomplished by combining high-throughput generation of affinity-purified antibodies with protein profiling in a multitude of tissues and cells assembled in tissue microarrays. Confocal microscopy analysis using human cell lines is performed for more detailed protein localization. The program hosts the Human Protein Atlas portal with expression profiles of human proteins in tissues and cells. The main objective of the resource centre is to produce specific antibodies to human target proteins using a high-throughput production method involving the cloning and protein expression of Protein Epitope Signature Tags (PrESTs). After purification, the antibodies are used to study expression profiles in cells and tissues and for functional analysis of the corresponding proteins in a wide range of platforms.
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The Global Proteome Machine (GPM) is a protein identification database. This data repository allows users to post and compare results. GPM's data is provided by contributors like The Informatics Factory, University of Michigan, and Pacific Northwestern National Laboratories. The GPM searchable databases are: GPMDB, pSYT, SNAP, MRM, PEPTIDE and HOT.
Human Proteinpedia is a community portal for sharing and integration of human protein data. This is a joint project between Pandey at Johns Hopkins University, and Institute of Bioinformatics, Bangalore. This portal allows research laboratories around the world to contribute and maintain protein annotations. Human Protein Reference Database (HPRD) integrates data, that is deposited in Human Proteinpedia along with the existing literature curated information in the context of an individual protein. All the public data contributed to Human Proteinpedia can be queried, viewed and downloaded. Data pertaining to post-translational modifications, protein interactions, tissue expression, expression in cell lines, subcellular localization and enzyme substrate relationships may be deposited.
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TopFIND is a protein-centric database for the annotation of protein termini currently in its third version. Non-canonical protein termini can be the result of multiple different biological processes, including pre-translational processes such as alternative splicing and alternative translation initiation or post-translational protein processing by proteases that cleave proteases as part of protein maturation or as a regulatory modification. Accordingly, protein termini evidence in TopFIND is inferred from other databases such as ENSEMBL transcripts, TISdb for alternative translation initiation, MEROPS for protein cleavage by proteases, and UniProt for canonical and protein isoform start sites.
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Datanator is an integrated database of genomic and biochemical data designed to help investigators find data about specific molecules and reactions in specific organisms and specific environments for meta-analyses and mechanistic models. Datanator currently includes metabolite concentrations, RNA modifications and half-lives, protein abundances and modifications, and reaction kinetics integrated from several databases and numerous publications. The Datanator website and REST API provide tools for extracting clouds of data about specific molecules and reactions in specific organisms and specific environments, as well as data about similar molecules and reactions in taxonomically similar organisms.
PDBj (Protein Data Bank Japan) provides a centralized PDB archive of macromolecular structures, integrated tools for data retrieval, visualization, and functional characterization. PDBj is supported by JST-NBDC and Osaka University.