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Found 28 result(s)
MassIVE is a community resource developed by the NIH-funded Center for Computational Mass Spectrometry to promote the global, free exchange of mass spectrometry data. MassIVE datasets can be assigned ProteomeXchange accessions to satisfy publication requirements.
SWATHAtlas is a repository of mass spectrometry data of the human proteome. The repository provides open access to libraries of SWATH-MS (Sequential Windowed Acquisition of All Theoretical Fragment Ion Mass Spectra) datasets. SWATH-MS is a method which combines both data-independent acquisition (DIA) and targeted data analysis techniques for the collection and storage of fragmentation spectra of peptides. Compared to techniques of selected reaction monitoring (SRM), SWATH-MS allows for a more extensive throughput of proteins in a sample to be targeted. The spectra collected in SWATHAtlas can be interpreted with the help of software such as OpenSWATH or Peakview.
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ProteomicsDB (https://www.ProteomicsDB.org) 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.
METLIN represents the largest MS/MS collection of data with the database generated at multiple collision energies and in positive and negative ionization modes. The data is generated on multiple instrument types including SCIEX, Agilent, Bruker and Waters QTOF mass spectrometers.
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.
The CPTAC Data Portal is the centralized repository for the dissemination of proteomic data collected by the Proteome Characterization Centers (PCCs) for the CPTAC program. The portal also hosts analyses of the mass spectrometry data (mapping of spectra to peptide sequences and protein identification) from the PCCs and from a CPTAC-sponsored common data analysis pipeline (CDAP).
The ProteomeXchange consortium has been set up to provide a single point of submission of MS proteomics data to the main existing proteomics repositories, and to encourage the data exchange between them for optimal data dissemination. Current members accepting submissions are: The PRIDE PRoteomics IDEntifications database at the European Bioinformatics Institute focusing mainly on shotgun mass spectrometry proteomics data PeptideAtlas/PASSEL focusing on SRM/MRM datasets.
The Yeast Resource Center provides access to data about mass spectrometry, yeast two-hybrid arrays, deconvolution florescence microscopy, protein structure prediction and computational biology. These services are provided to further the goal of a complete understanding of the chemical interactions required for the maintenance and faithful reproduction of a living cell. The observation that the fundamental biological processes of yeast are conserved among all eukaryotes ensures that this knowledge will shape and advance our understanding of living systems.
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 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.
This database will provide a central location for scientists to browse uniquely observed proteoforms and to contribute their own datasets. Top-down proteomics is a method of protein identification that uses an ion trapping mass spectrometer to store an isolated protein ion for mass measurement and tandem mass spectrometry analysis.
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In order to control access to the experimental data obtained at the ILL in a coherent and secure fashion, the ILL has recently developed a single portal for consulting, downloading and managing your data. Here “data” is understood to mean raw data (i.e. numor files), processed data, and meta-data (e.g. log files or “logs”).
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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.
Human Protein Reference Database (HPRD) has been established by a team of biologists, bioinformaticists and software engineers. This is a joint project between the PandeyLab at Johns Hopkins University, and Institute of Bioinformatics, Bangalore. HPRD is a definitive repository of human proteins. This database should serve as a ready reckoner for researchers in their quest for drug discovery, identification of disease markers and promote biomedical research in general. Human Proteinpedia (www.humanproteinpedia.org) is its associated data portal.
EuPathDB (formerly ApiDB) is an integrated database covering the eukaryotic pathogens in the genera Acanthamoeba, Annacaliia, Babesia, Crithidia, Cryptosporidium, Edhazardia, Eimeria, Encephalitozoon, Endotrypanum, Entamoeba, Enterocytozoon, Giardia, Gregarina, Hamiltosporidium, Leishmania, Nematocida, Neospora, Nosema, Plasmodium, Theileria, Toxoplasma, Trichomonas, Trypanosoma and Vavraia, Vittaforma). While each of these groups is supported by a taxon-specific database built upon the same infrastructure, the EuPathDB portal offers an entry point to all of these resources, and the opportunity to leverage orthology for searches across genera.
NIST Data Gateway - provides easy access to many of the NIST scientific and technical databases. These databases cover a broad range of substances and properties from many different scientific disciplines. The Gateway includes links to free online NIST data systems as well as to information on NIST PC databases available for purchase.
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jPOSTrepo (Japan ProteOme STandard Repository) is a repository of sharing MS raw/processed data. It consists of a high-speed file upload process, flexible file management system and easy-to-use interfaces. Users can release their "raw/processed" data via this site with a unique identifier number for the paper publication. Users also can suspend (or "embargo") their data until their paper is published. The file transfer from users’ computer to our repository server is very fast (roughly ten times faster than usual file transfer) and uses only web browsers – it does not require installing any additional software.
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.
HITRAN is an acronym for high-resolution transmission molecular absorption database. The HITRAN compilation of the SAO (HIgh resolution TRANmission molecular absorption database) is used for predicting and simulating transmission and emission of light in atmospheres. It is the world-standard database in molecular spectroscopy. The journal article describing it is the most cited reference in the geosciences. There are presently about 5000 HITRAN users world-wide. Its associated database HITEMP (high-temperature spectroscopic absorption parameters) is accessible by the HITRAN website.
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
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The Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) and the German Plant Phenotyping Network (DPPN) has jointly initiated the Plant Genomics and Phenomics Research Data Repository (PGP) as infrastructure to comprehensively publish plant research data [https://dx.doi.org/10.1093/database/baw033]. This covers in particular these cross-domain data sets that are not being published in central repositories because of its huge volume, unsupported data domain or scope, like image collections from plant phenotyping and microscopy, unassembled sequences, genotyping data, visualizations of complex morphological plant models, movies plant 3-D models, raw data from mass spectrometry, software, and documents. Accepted data is published as citable DOIs and core set of technical metadata is registered at DataCite. The used e!DAL-embedded Web frontend generates for each data set a landing page and supports an interactive exploration of available datasets. This long-term stable access to plant genomic and phenomic primary data records across domains and laboratories in one repository can empower researchers to reproduce already published analysis results as well as performing subsequent, advanced studies.