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Found 41 result(s)
The GHDx is our user-friendly and searchable data catalog for global health, demographic, and other health-related datasets. It provides detailed information about datasets ranging from censuses and surveys to health records and vital statistics, globally. It also serves as a platform for data owners to share their data with the public. The GDB Compare visualization, which allows the user to see rate of change in disease incidence, globally or by country, by age or across all ages, is especially powerful as a tool. Be sure to try adding a bottom chart, like the map, to augment the treemap that loads by default in the top chart.
The tree of life links all biodiversity through a shared evolutionary history. This project will produce the first online, comprehensive first-draft tree of all 1.8 million named species, accessible to both the public and scientific communities. Assembly of the tree will incorporate previously-published results, with strong collaborations between computational and empirical biologists to develop, test and improve methods of data synthesis. This initial tree of life will not be static; instead, we will develop tools for scientists to update and revise the tree as new data come in. Early release of the tree and tools will motivate data sharing and facilitate ongoing synthesis of knowledge.
The Research Collection is ETH Zurich's publication platform. It unites the functions of a university bibliography, an open access repository and a research data repository within one platform. Researchers who are affiliated with ETH Zurich, the Swiss Federal Institute of Technology, may deposit research data from all domains. They can publish data as a standalone publication, publish it as supplementary material for an article, dissertation or another text, share it with colleagues or a research group, or deposit it for archiving purposes. Research-data-specific features include flexible access rights settings, DOI registration and a DOI preview workflow, content previews for zip- and tar-containers, as well as download statistics and altmetrics for published data. All data uploaded to the Research Collection are also transferred to the ETH Data Archive, ETH Zurich’s long-term archive.
The Gene database provides detailed information for known and predicted genes defined by nucleotide sequence or map position. Gene supplies gene-specific connections in the nexus of map, sequence, expression, structure, function, citation, and homology data. Unique identifiers are assigned to genes with defining sequences, genes with known map positions, and genes inferred from phenotypic information. These gene identifiers are used throughout NCBI's databases and tracked through updates of annotation. Gene includes genomes represented by NCBI Reference Sequences (or RefSeqs) and is integrated for indexing and query and retrieval from NCBI's Entrez and E-Utilities systems.
ModelDB is a curated database of published models in the broad domain of computational neuroscience. It addresses the need for access to such models in order to evaluate their validity and extend their use. It can handle computational models expressed in any textual form, including procedural or declarative languages (e.g. C++, XML dialects) and source code written for any simulation environment. The model source code doesn't even have to reside inside ModelDB; it just has to be available from some publicly accessible online repository or WWW site.
<<<!!!<<< NCBI announced plans to retire the Clone DB web interface. Pursuant to this retirement, starting on May 27, 2019, all web pages associated with Clone DB and CloneFinder will redirect to this blog post https://ncbiinsights.ncbi.nlm.nih.gov/?s=clone+db. Links to Clone DB from the NCBI home page will also be going away. >>>!!!>>>
The Health and Retirement Study (HRS) is a longitudinal panel study that surveys a representative sample of more than 26,000 Americans over the age of 50 every two years. The study has collected information about income, work, assets, pension plans, health insurance, disability, physical health and functioning, cognitive functioning, genetic information and health care expenditures.
The Brain Transcriptome Database (BrainTx) project aims to create an integrated platform to visualize and analyze our original transcriptome data and publicly accessible transcriptome data related to the genetics that underlie the development, function, and dysfunction stages and states of the brain.
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Contains data on patients who have been tested for COVID-19 (whether positive or negative) in participating health institutions in Brazil. This initiative makes available three kinds of pseudonymized data: demographics (gender, year of birth, and region of residency), clinical and laboratory exams. Additional hospitalization information - such as data on transfers and outcomes - is provided when available. Clinical, lab, and hospitalization information is not limited to COVID-19 data, but covers all health events for these individuals, starting November 1st 2019, to allow for comorbidity studies. Data are deposited periodically, so that health information for a given individual is continuously updated to time of new version upload.
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DataverseNO (https://dataverse.no) is a curated, FAIR-aligned national generic repository for open research data from all academic disciplines. DataverseNO commits to facilitate that published data remain accessible and (re)usable in a long-term perspective. The repository is owned and operated by UiT The Arctic University of Norway. DataverseNO accepts submissions from researchers primarily from Norwegian research institutions. Datasets in DataverseNO are grouped into institutional collections as well as special collections. The technical infrastructure of the repository is based on the open source application Dataverse (https://dataverse.org), which is developed by an international developer and user community led by Harvard University.
Neuroimaging Tools and Resources Collaboratory (NITRC) is currently a free one-stop-shop environment for science researchers that need resources such as neuroimaging analysis software, publicly available data sets, and computing power. Since its debut in 2007, NITRC has helped the neuroscience community to use software and data produced from research that, before NITRC, was routinely lost or disregarded, to make further discoveries. NITRC provides free access to data and enables pay-per-use cloud-based access to unlimited computing power, enabling worldwide scientific collaboration with minimal startup and cost. With NITRC and its components—the Resources Registry (NITRC-R), Image Repository (NITRC-IR), and Computational Environment (NITRC-CE)—a researcher can obtain pilot or proof-of-concept data to validate a hypothesis for a few dollars.
Gemma is a database for the meta-analysis, re-use and sharing of genomics data, currently primarily targeted at the analysis of gene expression profiles. Gemma contains data from thousands of public studies, referencing thousands of published papers. Users can search, access and visualize co-expression and differential expression results.
The NCBI database of Genotypes and Phenotypes archives and distributes the results of studies that have investigated the interaction of genotype and phenotype, including genome-wide association studies, medical sequencing, molecular diagnostic assays, and association between genotype and non-clinical traits. The database provides summaries of studies, the contents of measured variables, and original study document text. dbGaP provides two types of access for users, open and controlled. Through the controlled access, users may access individual-level data such as phenotypic data tables and genotypes.
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SILVA is a comprehensive, quality-controlled web resource for up-to-date aligned ribosomal RNA (rRNA) gene sequences from the Bacteria, Archaea and Eukaryota domains alongside supplementary online services. In addition to data products, SILVA provides various online tools such as alignment and classification, phylogenetic tree calculation and viewer, probe/primer matching, and an amplicon analysis pipeline. With every full release a curated guide tree is provided that contains the latest taxonomy and nomenclature based on multiple references. SILVA is an ELIXIR Core Data Resource.
The Protein Data Bank (PDB) is an archive of experimentally determined three-dimensional structures of biological macromolecules that serves a global community of researchers, educators, and students. The data contained in the archive include atomic coordinates, crystallographic structure factors and NMR experimental data. Aside from coordinates, each deposition also includes the names of molecules, primary and secondary structure information, sequence database references, where appropriate, and ligand and biological assembly information, details about data collection and structure solution, and bibliographic citations. The Worldwide Protein Data Bank (wwPDB) consists of organizations that act as deposition, data processing and distribution centers for PDB data. Members are: RCSB PDB (USA), PDBe (Europe) and PDBj (Japan), and BMRB (USA). The wwPDB's mission is to maintain a single PDB archive of macromolecular structural data that is freely and publicly available to the global community.
The Neuroscience Information Framework is a dynamic index of data, materials, and tools. Please note, we do not accept direct data deposits, but if you wish to make your data repository or database available through our search, please contact us. An initiative of the NIH Blueprint for Neuroscience Research, NIF advances neuroscience research by enabling discovery and access to public research data and tools worldwide through an open source, networked environment.
The Electron Microscopy Data Bank (EMDB) is a public repository for electron microscopy density maps of macromolecular complexes and subcellular structures. It covers a variety of techniques, including single-particle analysis, electron tomography, and electron (2D) crystallography.
GigaDB primarily serves as a repository to host data and tools associated with articles published by GigaScience Press; GigaScience and GigaByte (both are online, open-access journals). GigaDB defines a dataset as a group of files (e.g., sequencing data, analyses, imaging files, software programs) that are related to and support a unit-of-work (article or study). GigaDB allows the integration of manuscript publication with supporting data and tools.