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Found 26 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.
The repository is no longer available. >>>!!!<<< 2021-01-25: no more access to California Water CyberInfrastructure >>>!!!<<<
For datasets big and small; Store your research data online. Quickly and easily upload files of any type and we will host your research data for you. Your experimental research data will have a permanent home on the web that you can refer to.
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.
The Wolfram Data Repository is a public resource that hosts an expanding collection of computable datasets, curated and structured to be suitable for immediate use in computation, visualization, analysis and more. Building on the Wolfram Data Framework and the Wolfram Language, the Wolfram Data Repository provides a uniform system for storing data and making it immediately computable and useful. With datasets of many types and from many sources, the Wolfram Data Repository is built to be a global resource for public data and data-backed publication.
THIN is a medical data collection scheme that collects anonymised patient data from its members through the healthcare software Vision. The UK Primary Care database contains longitudinal patient records for approximately 6% of the UK Population. The anonymised data collection, which goes back to 1994, is nationally representative of the UK population.
Additionally to the institutional repository, current St. Edward's faculty have the option of uploading their work directly to their own SEU accounts on stedwards.figshare.com. Projects created on Figshare will automatically be published on this website as well. For more information, please see documentation
EMSC collects real time parametric data (source parmaters and phase pickings) provided by 65 seismological networks of the Euro-Med region. These data are provided to the EMSC either by email or via QWIDS (Quake Watch Information Distribution System, developped by ISTI). The collected data are automatically archived in a database, made available via an autoDRM, and displayed on the web site. The collected data are automatically merged to produce automatic locations which are sent to several seismological institutes in order to perform quick moment tensors determination.
The FigShare service for University of Auckland, New Zealand was launched in January 2015 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 recieves a Digital Object identifier (DOI), which allows the data to be cited. 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.
Provided by the University Libraries, KiltHub is the comprehensive institutional repository and research collaboration platform for research data and scholarly outputs produced by members of Carnegie Mellon University and their collaborators. KiltHub collects, preserves, and provides stable, long-term global open access to a wide range of research data and scholarly outputs created by faculty, staff, and student members of Carnegie Mellon University in the course of their research and teaching.
The Immunology Database and Analysis Portal (ImmPort) archives clinical study and trial data generated by NIAID/DAIT-funded investigators. Data types housed in ImmPort include subject assessments i.e., medical history, concomitant medications and adverse events as well as mechanistic assay data such as flow cytometry, ELISA, ELISPOT, etc. --- You won't need an ImmPort account to search for compelling studies, peruse study demographics, interventions and mechanistic assays. But why stop there? What you really want to do is download the study, look at each experiment in detail including individual ELISA results and flow cytometry files. Perhaps you want to take those flow cytometry files for a test drive using FLOCK in the ImmPort flow cytometry module. To download all that interesting data you will need to register for ImmPort access.
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.
Online materials database (known as PAULING FILE project) with nearly 2 million entries: physical properties, crystal structures, phase diagrams, available via API, ready for modern data-intensive applications. The source of these entries are about 0.5M peer-reviewed publications in materials science, processed during the last 30 years by an international team of PhD editors. The results are presented online with a quick search interface. The basic access is provided for free.
BOARD (Bicocca Open Archive Research Data) is the institutional data repository of the University of Milano-Bicocca. BOARD is an open, free-to-use research data repository, which enables members of University of Milano-Bicocca to make their research data publicly available. By depositing their research data in BOARD researchers can: - Make their research data citable - Share their data privately or publicly - Ensure long-term storage for their data - Keep access to all versions - Link their article to their data
CORD is Cranfield University's research data repository, for secure preservation of institutional research data outputs. Cranfield is an exclusively postgraduate university that is a global leader for transformational research in technology and management. We are focused on the specialist themes of aerospace, defence and security, energy and power, environment and agrifood, manufacturing, transport systems, and water. The Cranfield School of Management is world leader in management education and research.
The ACEnano Knowledge Infrastructure facilitates access and sharing of methodology applied in nanosafety, starting with nanomaterials characterisation protocols developed or optimised within the ACEnano project.
MalaCards is an integrated database of human maladies and their annotations, modeled on the architecture and richness of the popular GeneCards database of human genes. MalaCards mines and merges varied web data sources to generate a computerized web card for each human disease. Each MalaCard contains disease specific prioritized annotative information, as well as links between associated diseases, leveraging the GeneCards relational database, search engine, and GeneDecks set-distillation tool. As proofs of concept of the search/distill/infer pipeline we find expected elucidations, as well as potentially novel ones.