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Found 1208 result(s)
GenBase is a genetic sequence database that accepts user submissions (mRNA, genomic DNAs, ncRNA, or small genomes such as organelles, viruses, plasmids, phages from any organism) and integrates data from INSDC.
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ARAMOB is a German project aiming at consolidating and mobilising data from systematic studies on the ecology of spiders in Germany through this online portal. The underlying data management is done with the modularized database system Diversity Workbench. This framework was enhanced as a virtual research environment for arachnology by including lists, thesaury and trans-modular functions and tools helpful for data management in studies of spider taxonomy and ecology. The ARAMOB database will serve as repository for ecological data on spiders from Germany, provided by the Arachnologische Gesellschaft (AraGes) in the sense of the German Federation for Biological Data (GFBio). Through the portal or direct use of the database with Diversity Workbench data will be available to members of the AraGes for ecological analyses of spider species and assemblages, e.g. occurence and distribution, phenology, habitat preferences, ecological preferences, indication of habitat quality, a.o.
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From April 2020 to March 2023, the Covid-19 Immunity Task Force (CITF) supported 120 studies to generate knowledge about immunity to SARS-CoV-2. The subjects addressed by these studies include the extent of SARS-CoV-2 infection in Canada, the nature of immunity, vaccine effectiveness and safety, and the need for booster shots among different communities and priority populations in Canada. The CITF Databank was developed to further enhance the impact of CITF funded studies by allowing additional research using the data collected from CITF-supported studies. The CITF Databank centralizes and harmonizes individual-level data from CITF-funded studies that have met all ethical requirements to deposit data in the CITF Databank and have completed a data sharing agreement. The CITF Databank is an internationally unique resource for sharing epidemiological and laboratory data from studies about SARS-CoV-2 immunity in different populations. The types of research that are possible with data from the CITF Databank include observational epidemiological studies, mathematical modelling research, and comparative evaluation of surveillance and laboratory methods.
Subject(s)
A domain-specific repository for the Life Sciences, covering the health, medical as well as the green life sciences. The repository services are primarily aimed at the Netherlands, but not exclusively.
NCBI Datasets is a continually evolving platform designed to provide easy and intuitive access to NCBI’s sequence data and metadata. NCBI Datasets is part of the NIH Comparative Genomics Resource (CGR). CGR facilitates reliable comparative genomics analyses for all eukaryotic organisms through an NCBI Toolkit and community collaboration.
MIDRC aims to develop a high-quality repository for medical images related to COVID-19 and associated clinical data, and develop and foster medical image-based artificial intelligence (AI) for use in the detection, diagnosis, prognosis, and monitoring of COVID-19.
Content type(s)
The Penn Integrated Neurodegenerative Disease Database (INDD) contains data from individuals with Alzheimer's disease, Parkinson's disease, frontotemporal dementia, and amyotrophic lateral sclerosis, who have been followed in research studies at the University of Pennsylvania. The database has been periodically described in publications (https://pubmed.ncbi.nlm.nih.gov/23978324/), with updates on the website. Researchers can request biosamples as well as clinical and biomarker data. Scientists work collaboratively to analyze the Integrative Neurodegenerative Disease Database (INDD) from the Center for Neurodegenerative Disease Research (CNDR) that tracks ~11,000 patients who attended one of four neurodegenerative disease centers at Penn.
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Institutional Repository of the University of Agriculture in Krakow (Poland). It includes the scientific achievements of the university's staff and students, including raw research data, as well as full texts of journals published by the University of Agriculture in Krakow.
The Central Neuroimaging Data Archive (CNDA) allows for sharing of complex imaging data to investigators around the world, through a simple web portal. The CNDA is an imaging informatics platform that provides secure data management services for Washington University investigators, including source DICOM imaging data sharing to external investigators through a web portal, cnda.wustl.edu. The CNDA’s services include automated archiving of imaging studies from all of the University’s research scanners, automated quality control and image processing routines, and secure web-based access to acquired and post-processed data for data sharing, in compliance with NIH data sharing guidelines. The CNDA is currently accepting datasets only from Washington University affiliated investigators. Through this platform, the data is available for broad sharing with researchers both internal and external to Washington University.. The CNDA overlaps with data in oasis-brains.org https://www.re3data.org/repository/r3d100012182, but CNDA is a larger data set.
figshare is the RDM system at the University. It is a cloud-based data repository that supports multiple file formats. Research data in the form of datasets, code, audio, images and more can be disseminated via the University's figshare. Citations can be traced for datasets (not just the final research output/article) and analytics will show who is looking at our research data around the world. figshare enables researchers to store research data in a secure way. The system is user-friendly, with easy access, and shareable with colleagues and collaborators on research projects. Where appropriate it enables researchers to make research data openly accessible.
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The Leibniz Data Manager (LDM) is a scientific repository for research data from the fields of science and technology. The service supports a better re-usability of research data for scientific projects. The LDM fosters the management and access to heterogeneous research data publications and assists researchers in the selection of relevant data sets for their respective disciplines. The LDM currently offers the following functions for the visualization of research data: · Supports data collections and publications with different formats. · Different views on the same data set (2D and 3D support). · Visualization of Auto CAD files. · Jupyter Notes for demonstrating live code. · RDF Description of data collections.
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The Preclinical Image DAtaset Repository (PIDAR) is a public repository of metadata information of preclinical image datasets from any imaging modality associated to peer-review publications. The metadata information are organized in a proper schema to create a standard metadata model for preclinical imaging.
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The Biodiversity Information System of Ecuador, SiB-Ec, is a technological tool that will become the core of the national information exchange network that promotes and facilitates interoperability, standardisation and implementation of guidelines for the management of data and information on biodiversity, through the National Catalogue of Biological Objects (CNOB), so that this information is available with different levels of access, and is used for the benefit of conservation, sustainable use of biodiversity, decision making and generation of public policy. SiB-Ec also makes it possible to manage the information generated on the country's Natural Heritage and to coordinate the efforts of the actors involved in the generation, management, publication and use of national biodiversity data and information. SiB-Ec also makes it possible to manage the information generated on the country's Natural Heritage and to coordinate the efforts of the actors involved in the generation, management, publication and use of national biodiversity data and information. Within SIB-Ec there is an IPT (The Integrated Publishing Toolkit) which is connected to GBIF for the exchange of biodiversity data in this network.
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The team have established the CardiacAI Data Repository that brings large amounts of Australian healthcare data together in a secure environment with strict conditions for use of these data with an appropriate level of oversight of research activities. The CardiacAI Data Repository collects de-identified EMR data about cardiovascular patients who are admitted to a group of urban and regional hospitals in NSW and links this with state-wide hospital and emergency deparment visit and mortality data and mobile-health remote monitoring data.
The mission of the GO Consortium is to develop a comprehensive, computational model of biological systems, ranging from the molecular to the organism level, across the multiplicity of species in the tree of life. The Gene Ontology (GO) knowledgebase is the world’s largest source of information on the functions of genes. This knowledge is both human-readable and machine-readable, and is a foundation for computational analysis of large-scale molecular biology and genetics experiments in biomedical research.
A central source for NEI biomedical digital objects including data sets, software and analytical workflow, metadata, standards, publications and more.
The BHIC is an archive repository in 's-Hertogenbosch. It is the Regional Historical Centre (RHC) of the province of North Brabant and was created by a merger in 2005 of the former state archives and several regional archives in Northeast Brabant. It currently comprises nine municipalities, two water boards, the province of North Brabant and several joint arrangements (GRs). The BHIC has the legal task of managing (digital) archives in good, orderly and accessible condition for the above-mentioned decentralised authorities. In addition, the BHIC also manages private archives.
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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
The Virtual Research Environment (VRE) is an open-source data management platform that enables medical researchers to store, process and share data in compliance with the European Union (EU) General Data Protection Regulation (GDPR). The VRE addresses the present lack of digital research data infrastructures fulfilling the need for (a) data protection for sensitive data, (b) capability to process complex data such as radiologic imaging, (c) flexibility for creating own processing workflows, (d) access to high performance computing. The platform promotes FAIR data principles and reduces barriers to biomedical research and innovation. The VRE offers a web portal with graphical and command-line interfaces, segregated data zones and organizational measures for lawful data onboarding, isolated computing environments where large teams can collaboratively process sensitive data privately, analytics workbench tools for processing, analyzing, and visualizing large datasets, automated ingestion of hospital data sources, project-specific data warehouses for structured storage and retrieval, graph databases to capture and query ontology-based metadata, provenance tracking, version control, and support for automated data extraction and indexing. The VRE is based on a modular and extendable state-of-the art cloud computing framework, a RESTful API, open developer meetings, hackathons, and comprehensive documentation for users, developers, and administrators. The VRE with its concerted technical and organizational measures can be adopted by other research communities and thus facilitates the development of a co-evolving interoperable platform ecosystem with an active research community.
ODC-TBI is a community platform to Share Data, Publish Data with a DOI, and get Citations. Advancing Traumatic Brain Injury research through sharing of data from basic and clinical research.
HI HOPES aims is to provide free home based support and information without bias to every family with an infant or toddler with hearing loss. Through an early intervention framework of care, support, information and partnership in a culturally sensitive, community based manner to allow we aim to empower the family in their home environment and help the baby with a hearing loss to reach her/his full potential.