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Found 306 result(s)
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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.
Project Achilles is a systematic effort aimed at identifying and cataloging genetic vulnerabilities across hundreds of genomically characterized cancer cell lines. The project uses genome-wide genetic perturbation reagents (shRNAs or Cas9/sgRNAs) to silence or knock-out individual genes and identify those genes that affect cell survival. Large-scale functional screening of cancer cell lines provides a complementary approach to those studies that aim to characterize the molecular alterations (e.g. mutations, copy number alterations) of primary tumors, such as The Cancer Genome Atlas (TCGA). The overall goal of the project is to identify cancer genetic dependencies and link them to molecular characteristics in order to prioritize targets for therapeutic development and identify the patient population that might benefit from such targets. Project Achilles data is hosted on the Cancer Dependency Map Portal (DepMap) where it has been harmonized with our genomics and cellular models data. You can access the latest and all past datasets here: https://depmap.org/portal/download/all/
Virtual Fly Brain (VFB) - an interactive tool for neurobiologists to explore the detailed neuroanatomy, neuron connectivity and gene expression of the Drosophila melanogaster CNS.
>>> !!! the repository is offline !!! <<< More information see: https://dknet.org/about/NURSA_Archive All NURSA-biocurated transcriptomic datasets have been preserved for data mining in SPP through an enhanced and expanded version of Transcriptomine named Ominer. To access these datasets, dkNET provides users with the information of 527 transcriptomic datasets that contain data related to nuclear receptors and nuclear receptor coregulators in the NURSA Datasets table view and redirects users to the current SPP dataset page. Once users find the specific dataset of research interest, users can download the dataset by clicking DOI and then clicking the Download Dataset button at the Signaling Pathways Project webpage. See https://www.re3data.org/repository/r3d100013650
<<<!!!<<< OFFLINE >>>!!!>>> A recent computer security audit has revealed security flaws in the legacy HapMap site that require NCBI to take it down immediately. We regret the inconvenience, but we are required to do this. That said, NCBI was planning to decommission this site in the near future anyway (although not quite so suddenly), as the 1,000 genomes (1KG) project has established itself as a research standard for population genetics and genomics. NCBI has observed a decline in usage of the HapMap dataset and website with its available resources over the past five years and it has come to the end of its useful life. The International HapMap Project is a multi-country effort to identify and catalog genetic similarities and differences in human beings. Using the information in the HapMap, researchers will be able to find genes that affect health, disease, and individual responses to medications and environmental factors. The Project is a collaboration among scientists and funding agencies from Japan, the United Kingdom, Canada, China, Nigeria, and the United States. All of the information generated by the Project will be released into the public domain. The goal of the International HapMap Project is to compare the genetic sequences of different individuals to identify chromosomal regions where genetic variants are shared. By making this information freely available, the Project will help biomedical researchers find genes involved in disease and responses to therapeutic drugs. In the initial phase of the Project, genetic data are being gathered from four populations with African, Asian, and European ancestry. Ongoing interactions with members of these populations are addressing potential ethical issues and providing valuable experience in conducting research with identified populations. Public and private organizations in six countries are participating in the International HapMap Project. Data generated by the Project can be downloaded with minimal constraints. The Project officially started with a meeting in October 2002 (https://www.genome.gov/10005336/) and is expected to take about three years.
<<<!!!<<< This repository is no longer available. >>>!!!>>> BioVeL is a virtual e-laboratory that supports research on biodiversity issues using large amounts of data from cross-disciplinary sources. BioVeL supports the development and use of workflows to process data. It offers the possibility to either use already made workflows or create own. BioVeL workflows are stored in MyExperiment - Biovel Group http://www.myexperiment.org/groups/643/content. They are underpinned by a range of analytical and data processing functions (generally provided as Web Services or R scripts) to support common biodiversity analysis tasks. You can find the Web Services catalogued in the BiodiversityCatalogue.
TAED is a database of phylogenetically indexed gene families. It contains multiple sequence alignments from MAFFT1, maximum likelihood phylogenetic trees from PhyML2, bootstrap values for each node, dN/dS ratios for each lineage from the free ratios model in PAML3, and labels for each node of speciation or duplication from gene tree/species tree reconciliation using SoftParsMap4. The phylogenetic indexing enables simultaneous viewing of lineages with high dN/dS that occurred along the same species tree branches. Resources from the Protein Data Bank (PDB) and the Kyoto Encyclopedia of Genes and Genomes (KEGG)5, have been incorporated into the TAED analysis to detect substitutions along each branch within the phylogenetic tree and to assess selection within pathways.
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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.
TreeGenes is a genomic, phenotypic, and environmental data resource for forest tree species. The TreeGenes database and Dendrome project provide custom informatics tools to manage the flood of information.The database contains several curated modules that support the storage of data and provide the foundation for web-based searches and visualization tools. GMOD GUI tools such as CMAP for genetic maps and GBrowse for genome and transcriptome assemblies are implemented here. A sample tracking system, known as the Forest Tree Genetic Stock Center, sits at the forefront of most large-scale projects. Barcode identifiers assigned to the trees during sample collection are maintained in the database to identify an individual through DNA extraction, resequencing, genotyping and phenotyping. DiversiTree, a user-friendly desktop-style interface, queries the TreeGenes database and is designed for bulk retrieval of resequencing data. CartograTree combines geo-referenced individuals with relevant ecological and trait databases in a user-friendly map-based interface. ---- The Conifer Genome Network (CGN) is a virtual nexus for researchers working in conifer genomics. The CGN web site is maintained by the Dendrome Project at the University of California, Davis.
NKN is now Research Computing and Data Services (RCDS)! We provide data management support for UI researchers and their regional, national, and international collaborators. This support keeps researchers at the cutting-edge of science and increases our institution's competitiveness for external research grants. Quality data and metadata developed in research projects and curated by RCDS (formerly NKN) is a valuable, long-term asset upon which to develop and build new research and science.
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GnpIS is a multispecies integrative information system dedicated to plant and fungi pests. It bridges genetic and genomic data, allowing researchers access to both genetic information (e.g. genetic maps, quantitative trait loci, association genetics, markers, polymorphisms, germplasms, phenotypes and genotypes) and genomic data (e.g. genomic sequences, physical maps, genome annotation and expression data) for species of agronomical interest. GnpIS is used by both large international projects and plant science departments at the French National Research Institute for Agriculture, Food and Environment. It is regularly improved and released several times per year. GnpIS is accessible through a web portal and allows to browse different types of data either independently through dedicated interfaces or simultaneously using a quick search ('google like search') or advanced search (Biomart, Galaxy, Intermine) tools.
The figshare service for The Open University was launched in 2016 and allows researchers to store, share and publish research data. It helps the research data to be accessible by storing metadata alongside datasets. Additionally, every uploaded item receives a Digital Object Identifier (DOI), which allows the data to be citable and sustainable. If there are any ethical or copyright concerns about publishing a certain dataset, it is possible to publish the metadata associated with the dataset to help discoverability while sharing the data itself via a private channel through manual approval.
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'Redape' is a digital repository that aims to preserve and disseminate research data produced by the Brazilian Agricultural Research Corporation - Embrapa. It allows the organization, management and publication of data in accordance with the FAIR principles.
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Plastics are widely used in our economy and each year, at least 350-400 million tons are being produced at a global level. Due to poor recycling and low circular use, tens of millions of tons accumulate annually in marine and terrestrial environments. While it has become obvious that micro and macroplastics contaminate our environments recent research has identified few bacteria and fungi actively degrading plastics by enzymatic reactions. In general these are promiscuous enzymes (hydrolases) acting on low crystaline and mostly low density polymers of PET, ester-based PUR and oligomers of PA. Notably today, no enzymes have been characterized on a biochemical level for polymeric and crystaline PE, ether-based PUR, PS, PVC, PP. While many publications report on plastic degradation often, no convincing biochemical data have been published. Therefore the PAZy database lists exclusively biochemically characterized plastic-active enzymes. Predicted and putative enzymes that were not characterized on a biochemical, functional or structural level are not included in the PAZy database. The entries are manually curated.
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Sextant is a marine and coastal geographic data infrastructure. It is operated by Scientific Information Systems for the Sea (SISMER) of Ifremer (https://www.ifremer.fr/). Sextant aims to document, disseminate and promote a catalog of data related to the marine environment. For Ifremer's laboratories and partners, as well as for national and European actors working in the marine and coastal field, Sextant provides tools that promote and facilitate the archiving, consultation and availability of these geographical data. Data published by Sextant are available free or restricted. They can be used in accordance with the terms of the Creative Commons license selected by the author of data. Sextant infrastructure and the technologies used are in line with the implementation of the INSPIRE Directive and make it possible to follow the Open Data approach. Some data set published by Sextant has a DOI which enables it to be cited in a publication in a reliable and sustainable way. The long-term preservation of data filed in Sextant is ensured by Ifremer infrastructure.
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The public MorpheusML model repository collects, curates, documents and tests computational models for multi-scale and multicellular biological systems. Model must be encoded in the model description language MorpheusML. Subsections of the repository distinguish published models from contributed non-published and example models. New models are simulated in Morpheus or Artistoo independently from the authors and results are compared to published results. Successful reproduction is documented on the model's webpage. Models in this repository are included into the CI and test pipelines for each release of the model simulator Morpheus to check and guarantee reproducibility of results across future simulator updates. The model’s webpage provides a History-link to all past model versions and edits that are automatically tracked via Git. Each model is registered with a unique and persistent ID of the format M..... The model description page (incl. the biological context and key results of that model), the model’s XML file, the associated paper, and all further files (often simulation result videos) connected with that model can be retrieved via a persistent URL of the format https://identifiers.org/morpheus/M..... - for technical details on the citable ModelID please see https://registry.identifiers.org/registry/morpheus - for the model definition standard MorpheusML please see https://doi.org/10.25504/FAIRsharing.78b6a6 - for the model simulator Morpheus please see https://morpheus.gitlab.io - for the model simulator Artistoo please see https://artistoo.net/converter.html
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The Crop EST Database (CR-EST) is a public available online resource providing access to sequence, classification, clustering, and annotation data of crop EST projects at the IPK. A view of these information give the summarized numbers about genomic data of species listed in the adjacent table.
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.