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Found 188 result(s)
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 comounds detected by mass spectrometry.MassBank system is originally designed for public sharing of reference mass spectra for metabolite identification. It is also useful for their in-house or local sharing. Recently it finds another application; sharing mass spectra of unknown metabolites for metabolite profiling. The IPB is operating the first european MassBank site, that is part of the consortial MassBank Project. You can access both the set of IPB Tandem-MS and Ion Trap spectra, as well as the other massbank sites.
The European Genome-phenome Archive (EGA) is designed to be a repository for all types of sequence and genotype experiments, including case-control, population, and family studies. We will include SNP and CNV genotypes from array based methods and genotyping done with re-sequencing methods. The EGA will serve as a permanent archive that will archive several levels of data including the raw data (which could, for example, be re-analysed in the future by other algorithms) as well as the genotype calls provided by the submitters. We are developing data mining and access tools for the database. For controlled access data, the EGA will provide the necessary security required to control access, and maintain patient confidentiality, while providing access to those researchers and clinicians authorised to view the data. In all cases, data access decisions will be made by the appropriate data access-granting organisation (DAO) and not by the EGA. The DAO will normally be the same organisation that approved and monitored the initial study protocol or a designate of this approving organisation. The European Genome-phenome Archive (EGA) allows you to explore datasets from genomic studies, provided by a range of data providers. Access to datasets must be approved by the specified Data Access Committee (DAC).
FRED is an online database consisting of hundreds of thousands of economic data time series from scores of national, international, public, and private sources. FRED, created and maintained by the Research Department at the Federal Reserve Bank of St. Louis, goes far beyond simply providing data: It combines data with a powerful mix of tools that help the user understand, interact with, display, and disseminate the data. In essence, FRED helps users tell their data stories.
The Solar Dynamics Observatory (SDO) studies the solar atmosphere on small scales of space and time, in multiple wavelengths. This is a searchable database of all SDO data, including citizen scientist images, space weather and near real time data, and helioseismology data.
virus mentha archives evidence about viral interactions 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. virus 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". virus 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. virus mentha offers direct access to viral families such as: Orthomyxoviridae, Orthoretrovirinae and Herpesviridae plus, it offers the unique possibility of searching by host organism. The website and the graphical application are designed to make the data stored in virus mentha accessible and analysable to all users.virus mentha superseeds VirusMINT. The Source databases are: MINT, DIP, IntAct, MatrixDB, BioGRID.
JHU has stopped collecting data as of 03/10/2023 After three years of around-the-clock tracking of COVID-19 data from around the world, Johns Hopkins has discontinued the Coronavirus Resource Center’s operations. The site’s two raw data repositories will remain accessible for information collected from 1/22/20 to 3/10/23 on cases, deaths, vaccines, testing and demographics. Coronavirus COVID-19 Global Cases by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University (JHU). Johns Hopkins experts in global public health, infectious disease, and emergency preparedness have been at the forefront of the international response to COVID-19. This website is a resource to help advance the understanding of the virus, inform the public, and brief policymakers in order to guide a response, improve care, and save lives. All data collected and displayed are made freely available through a GitHub repository https://github.com/CSSEGISandData/COVID-19, along with the feature layers of the dashboard, which are now included in the ESRI Living Atlas: https://livingatlas.arcgis.com/en/home/
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.
The Mouse Phenome Database (MPD; phenome.jax.org) has characterizations of hundreds of strains of laboratory mice to facilitate translational discoveries and to assist in selection of strains for experimental studies.
The Basis Set Exchange (BSE) provides a web-based user interface for downloading and uploading Gaussian-type (GTO) basis sets, including effective core potentials (ECPs), from the EMSL Basis Set Library. It provides an improved user interface and capabilities over its predecessor, the EMSL Basis Set Order Form, for exploring the contents of the EMSL Basis Set Library. The popular Basis Set Order Form and underlying Basis Set Library were originally developed by Dr. David Feller and have been available from the EMSL webpages since 1994.
BsubCyc is a model-organism database for the bacterium Bacillus subtilis and is based on the updated B. subtilis 168 genome sequence and annotation published by Barbe et al. in 2009. Gene function annotations are being updated when new literature is available. Subscriptions are now required to access BsubCyc. For more information on obtaining a subscription, click here: http://www.phoenixbioinformatics.org/biocyc/subscriptions.html
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SMHI's observation stations collect large quantities of data, including temperature, precipitation, wind, air pressure, lightning, solar radiation and ozone. Satellites and radar installations are also important sources. Data is presented continuously on smhi.se and used in SMHI's various weather services. In the Explorer SMHI’s data ( http://opendata-catalog.smhi.se/explore/ ) you find data available with open access (in Swedish). Information in English on Oceanographic observations, Model data (HIROMB BS01), Machine to machine – feeds, and Conditions of use.
SLAPIS is an integrated Flood Early Warning System that aims to promote decision-making and behavioral changes from reactive to proactive at several levels, from the community to the administration, for the reduction of flood risk in the Communes of the Sirba (main tributary of the Niger River and cause of the main floods in the region)
OASIS-3 is the latest release in the Open Access Series of Imaging Studies (OASIS) that aimed at making neuroimaging datasets freely available to the scientific community. By compiling and freely distributing this multi-modal dataset, we hope to facilitate future discoveries in basic and clinical neuroscience. Previously released data for OASIS-Cross-sectional (Marcus et al, 2007) and OASIS-Longitudinal (Marcus et al, 2010) have been utilized for hypothesis driven data analyses, development of neuroanatomical atlases, and development of segmentation algorithms. OASIS-3 is a longitudinal neuroimaging, clinical, cognitive, and biomarker dataset for normal aging and Alzheimer’s Disease. The OASIS datasets hosted by central.xnat.org provide the community with open access to a significant database of neuroimaging and processed imaging data across a broad demographic, cognitive, and genetic spectrum an easily accessible platform for use in neuroimaging, clinical, and cognitive research on normal aging and cognitive decline. All data is available via www.oasis-brains.org.
The BioCyc database collection of Pathway/Genome Databases (PGDBs) provides a reference on the genomes and metabolic pathways of thousands of sequenced organisms. BioCyc PGDBs are generated by software that predict the metabolic pathways of completely sequenced organisms, predict which genes code for missing enzymes in metabolic pathways, and predict operons. BioCyc also integrates information from other bioinformatics databases, such as protein feature and Gene Ontology information from UniProt. The BioCyc website provides a suite of software tools for database searching and visualization, for omics data analysis, and for comparative genomics and comparative pathway questions. From 2016 on, access to the EcoCyc and MetaCyc databases will remain free. Subscriptions to the other 7,600 BioCyc databases will be available to institutions (e.g., libraries), and to individuals. Access to licensed databases via: https://biocyc.org/Product-summary.shtml.
OpenML is an open ecosystem for machine learning. By organizing all resources and results online, research becomes more efficient, useful and fun. OpenML is a platform to share detailed experimental results with the community at large and organize them for future reuse. Moreover, it will be directly integrated in today’s most popular data mining tools (for now: R, KNIME, RapidMiner and WEKA). Such an easy and free exchange of experiments has tremendous potential to speed up machine learning research, to engender larger, more detailed studies and to offer accurate advice to practitioners. Finally, it will also be a valuable resource for education in machine learning and data mining.