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Found 35 result(s)
!!! >>> intrepidbio.com expired <<< !!!! Intrepid Bioinformatics serves as a community for genetic researchers and scientific programmers who need to achieve meaningful use of their genetic research data – but can’t spend tremendous amounts of time or money in the process. The Intrepid Bioinformatics system automates time consuming manual processes, shortens workflow, and eliminates the threat of lost data in a faster, cheaper, and better environment than existing solutions. The system also provides the functionality and community features needed to analyze the large volumes of Next Generation Sequencing and Single Nucleotide Polymorphism data, which is generated for a wide range of purposes from disease tracking and animal breeding to medical diagnosis and treatment.
Brain Image Library (BIL) is an NIH-funded public resource serving the neuroscience community by providing a persistent centralized repository for brain microscopy data. Data scope of the BIL archive includes whole brain microscopy image datasets and their accompanying secondary data such as neuron morphologies, targeted microscope-enabled experiments including connectivity between cells and spatial transcriptomics, and other historical collections of value to the community. The BIL Analysis Ecosystem provides an integrated computational and visualization system to explore, visualize, and access BIL data without having to download it.
The figshare service for the University of Sheffield 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.
The CancerData site is an effort of the Medical Informatics and Knowledge Engineering team (MIKE for short) of Maastro Clinic, Maastricht, The Netherlands. Our activities in the field of medical image analysis and data modelling are visible in a number of projects we are running. CancerData is offering several datasets. They are grouped in collections and can be public or private. You can search for public datasets in the NBIA (National Biomedical Imaging Archive) image archives without logging in.
EMPIAR, the Electron Microscopy Public Image Archive, is a public resource for raw, 2D electron microscopy images. Here, you can browse, upload, download and reprocess the thousands of raw, 2D images used to build a 3D structure. The purpose of EMPIAR is to provide an easy access to the state-of-the-art raw data to facilitate methods development and validation, which will lead to better 3D structures. It complements the Electron Microscopy Data Bank (EMDB), where 3D images are stored, and uses the fault-tolerant Aspera platform for data transfers
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The IDR makes datasets that have never previously been accessible publicly available, allowing the community to search, view, mine and even process and analyze large, complex, multidimensional life sciences image data. Sharing data promotes the validation of experimental methods and scientific conclusions, the comparison with new data obtained by the global scientific community, and enables data reuse by developers of new analysis and processing tools.
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>>>!!!<<< Data originally published in the JCB DataViewer has been moved BioStudies. Please note that while the majority of data were moved, some authors opted to remove their data completely. >>>!!!<<< Migrated data can be found at https://www.ebi.ac.uk/biostudies/JCB/studies. Screen data are available in the Image Data Resource repository. http://idr.openmicroscopy.org/webclient/?experimenter=-1 >>>!!!<<< The DataViewer was decommissioned in 2018 as the journal evolved to an all-encompassing archive policy towards original source data and as new data repositories that go beyond archiving data and allow investigators to make new connections between datasets, potentially driving discovery, emerged. JCB authors are encouraged to make available all datasets included in the manuscript from the date of online publication either in a publicly available database or as supplemental materials hosted on the journal website. We recommend that our authors store and share their data in appropriate publicly available databases based on data type and/or community standard. >>>!!!<<<
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ZB MED's Repository for Life Sciences offers authors the chance to publish their scientific texts and research data from the fields of medicine, health, nutritional, environmental and agricultural sciences. In accordance with the principles of Open Access, these publications can be accessed over the Internet without restrictions. There is no charge to publish, archive or use the documents.
Country
Swedish National Data Service (SND) is a research data infrastructure designed to assist researchers in preserving, maintaining, and disseminating research data in a secure and sustainable manner. The SND Search function makes it easy to find, use, and cite research data from a variety of scientific disciplines. Together with an extensive network of almost 40 Swedish higher education institutions and other research organisations, SND works for increased access to research data, nationally as well as internationally.
Country
The UWA Profiles and Research Repository contains research publications, research datasets, theses, equipment, grants and activities created by researchers and postgraduates affiliated with the University of Western Australia (UWA). It is managed by the University Library and provides access to research datasets held at UWA. The information about each dataset has been provided by UWA research groups. Dataset metadata is harvested into Research Data Australia (RDA) https://researchdata.edu.au/.
Country
Federation.figshare is a collaborative digital repository for Federation researchers, professional staff and Higher Degree by Research students to store, share and publish their digital files. It accepts all forms of digital research outputs including audio, video, PDF, images, code, datasets, presentations and more.
Funded by the National Science Foundation (NSF) and proudly operated by Battelle, the National Ecological Observatory Network (NEON) program provides open, continental-scale data across the United States that characterize and quantify complex, rapidly changing ecological processes. The Observatory’s comprehensive design supports greater understanding of ecological change and enables forecasting of future ecological conditions. NEON collects and processes data from field sites located across the continental U.S., Puerto Rico, and Hawaii over a 30-year timeframe. NEON provides free and open data that characterize plants, animals, soil, nutrients, freshwater, and the atmosphere. These data may be combined with external datasets or data collected by individual researchers to support the study of continental-scale ecological change.
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.
ETH Data Archive is ETH Zurich's long-term preservation solution for digital information such as research data, digitised content, archival records, or images. It serves as the backbone of data curation and for most of its content, it is a “dark archive” without public access. In this capacity, the ETH Data Archive also archives the content of ETH Zurich’s Research Collection which is the primary repository for members of the university and the first point of contact for publication of data at ETH Zurich. All data that was produced in the context of research at the ETH Zurich, can be published and archived in the Research Collection. An automated connection to the ETH Data Archive in the background ensures the medium to long-term preservation of all publications and research data. Direct access to the ETH Data Archive is intended only for customers who need to deposit software source code within the framework of ETH transfer Software Registration. Open Source code packages and other content from legacy workflows can be accessed via ETH Library @ swisscovery (https://library.ethz.ch/en/).
The OpenNeuro project (formerly known as the OpenfMRI project) was established in 2010 to provide a resource for researchers interested in making their neuroimaging data openly available to the research community. It is managed by Russ Poldrack and Chris Gorgolewski of the Center for Reproducible Neuroscience at Stanford University. The project has been developed with funding from the National Science Foundation, National Institute of Drug Abuse, and the Laura and John Arnold Foundation.
The KNB Data Repository is an international repository intended to facilitate ecological, environmental and earth science research in the broadest senses. For scientists, the KNB Data Repository is an efficient way to share, discover, access and interpret complex ecological, environmental, earth science, and sociological data and the software used to create and manage those data. Due to rich contextual information provided with data in the KNB, scientists are able to integrate and analyze data with less effort. The data originate from a highly-distributed set of field stations, laboratories, research sites, and individual researchers. The KNB supports rich, detailed metadata to promote data discovery as well as automated and manual integration of data into new projects. The KNB supports a rich set of modern repository services, including the ability to assign Digital Object Identifiers (DOIs) so data sets can be confidently referenced in any publication, the ability to track the versions of datasets as they evolve through time, and metadata to establish the provenance relationships between source and derived data.
San Raffaele Open Research Data Repository (ORDR) is an institutional platform which allows to safely store, preserve and share research data. ORDR is endowed with the essential characteristics of trusted repositories, as it ensures: a) open or restricted access to contents, with persistent unique identifiers to enable referencing and citation; b) a comprehensive set of Metadata fields to enable discovery and reuse; c) provisions to safeguard integrity, authenticity and long-term preservation of deposited data.
Modern signal processing and machine learning methods have exciting potential to generate new knowledge that will impact both physiological understanding and clinical care. Access to data - particularly detailed clinical data - is often a bottleneck to progress. The overarching goal of PhysioNet is to accelerate research progress by freely providing rich archives of clinical and physiological data for analysis. The PhysioNet resource has three closely interdependent components: An extensive archive ("PhysioBank"), a large and growing library of software ("PhysioToolkit"), and a collection of popular tutorials and educational materials