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Found 23 result(s)
The PAIN Repository is a recently funded NIH initiative, which has two components: an archive for already collected imaging data (Archived Repository), and a repository for structural and functional brain images and metadata acquired prospectively using standardized acquisition parameters (Standardized Repository) in healthy control subjects and patients with different types of chronic pain. The PAIN Repository provides the infrastructure for storage of standardized resting state functional, diffusion tensor imaging and structural brain imaging data and associated biological, physiological and behavioral metadata from multiple scanning sites, and provides tools to facilitate analysis of the resulting comprehensive data sets.
Blackfynn Discover is a repository for Neurology and Neuroscience datasets. This repository, funded by DARPA, the NIH, and others, provides a user-friendly solution for publishing large, complex datasets is a scalable and sustainable way. The platform aims to make data available in a meaningful way and to drive adoption of cloud-based analysis over large datasets.
This site provides information about the NIH MRI Study of Normal Brain Development (Pediatric MRI Study) and resulting Pediatric MRI Data Repository. This website serves as the portal through which data can be obtained by qualified researchers. The overarching goal of the Pediatric MRI Study is to foster a better understanding of normal brain maturation as a basis for understanding atypical brain development associated with a variety of disorders and diseases.
The repository of the Donders Institute for Brain, Cognition and Behaviour at the Radboud University is used to manage, share and publish neuroscience and neuroimaging data, including MRI, EEG, MEG and other types of research data.
The National Database for Autism Research (NDAR) is an NIH-funded research data repository that aims to accelerate progress in autism spectrum disorders (ASD) research through data sharing, data harmonization, and the reporting of research results. NDAR also serves as a scientific community platform and portal to multiple other research repositories, allowing for aggregation and secondary analysis of data. NDAR combines the function of a data repository, which holds genetic, phenotypic, clinical, and medical imaging data, and the function of a scientific community platform, which defines the standard tools and policies to integrate the computational resources developed by scientific research institutions, private foundations, and other federal and state agencies supporting ASD research. Furthermore, NDAR is working to develop the means to connect relevant repositories together through data federation.
NeuroMorpho.Org is a centrally curated inventory of digitally reconstructed neurons associated with peer-reviewed publications. It contains contributions from over 80 laboratories worldwide and is continuously updated as new morphological reconstructions are collected, published, and shared. To date, NeuroMorpho.Org is the largest collection of publicly accessible 3D neuronal reconstructions and associated metadata which can be used for detailed single cell simulations.
XNAT CENTRAL is a publicly accessible datasharing portal at Washinton University Medical School using XNAT software. XNAT provides neuroimaging data through a web interface and a customizable open source platform. XNAT facilitates data uploads and downloads for data sharing, processing and organization.
Virtual Fly Brain (VFB) - an interactive tool for neurobiologists to explore the detailed neuroanatomy, neuron connectivity and gene expression of the adult Drosophila melanogaster brain.
The Neuroscience Information Framework is a dynamic inventory of Web-based neuroscience resources: data, materials, and tools accessible via any computer connected to the Internet. 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.
RDoCdb is an informatics platform for the sharing of human subjects data generated by investigators as part of the NIMH's Research Domain Criteria initiative, and to support this initiative's aims. It also accepts and shares appropriate data related to mental health from other sources.
LONI’s Image and Data Archive (IDA) is a secure data archiving system. The IDA uses a robust infrastructure to provide researchers with a flexible and simple interface for de-identifying, searching, retrieving, converting, and disseminating their biomedical data. With thousands of investigators across the globe and more than 21 million data downloads to data, the IDA guarantees reliability with a fault-tolerant network comprising multiple switches, routers, and Internet connections to prevent system failure.
***<<<!!!>>> *** Stated 2017-08-28: To accommodate a wider scope of ophthalmic data, we launched our new Rotterdam Ophthalmic Data Repository. Please visit http://www.rodrep.com/ for all data sets. *** The ORGIDS site will no longer be updated! ***<<<!!!>>>***Through this portal, we will make data sets available that result from our glaucoma research. This includes visual fields, various imaging modalities and other data from both glaucomatous and normal subjects.The data was acquired during more than a decade.
Psi Open Data is an open repository for parapsychology research data, operated by the Society for Psychical Research. The datasets may be freely used, modified, and shared by anyone – subject, at most, to the requirement to attribute and/or share-alike (see the license attached to each dataset for details).
ALSoD is a freely available database that has been transformed from a single gene storage facility recording mutations in the SOD1 gene to a multigene ALS bioinformatics repository and analytical instrument combining genotype, phenotype, and geographical information with associated analysis tools. These include a comparison tool to evaluate genes side by side or jointly with user configurable features, a pathogenicity prediction tool using a combination of computational approaches to distinguish variants with nonfunctional characteristics from disease-associated mutations with more dangerous consequences, and a credibility tool to enable ALS researchers to objectively assess the evidence for gene causation in ALS. Furthermore, integration of external tools, systems for feedback, annotation by users, and two-way links to collaborators hosting complementary databases further enhance the functionality of ALSoD.
>>> !!!!! The Portal is no longer available. !!!! >>> The CARMEN pilot project seeks to create a virtual laboratory for experimental neurophysiology, enabling the sharing and collaborative exploitation of data, analysis code and expertise. This study by the DCC contributes to an understanding of the data curation requirements of the eScience community, through its extended observation of the CARMEN neurophysiology community’s specification and selection of solutions for the organisation, access and curation of digital research output.
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The German Neuroinformatics Node's data infrastructure (GIN) services provide a platform for comprehensive and reproducible management and sharing of neuroscience data. Building on well established versioning technology, GIN offers the power of a web based repository management service combined with a distributed file storage. The service addresses the range of research data workflows starting from data analysis on the local workstation to remote collaboration and data publication.
The National Database for Clinical Trials Related to Mental Illness (NDCT) is an informatics platform for the sharing of human subjects data from all clinical trials funded by the National Institute of Mental Health (NIMH).
The ENCODE Encyclopedia organizes the most salient analysis products into annotations, and provides tools to search and visualize them. The Encyclopedia has two levels of annotations: Integrative-level annotations integrate multiple types of experimental data and ground level annotations. Ground-level annotations are derived directly from the experimental data, typically produced by uniform processing pipelines.
The Brain Biodiversity Bank refers to the repository of images of and information about brain specimens contained in the collections associated with the National Museum of Health and Medicine at the Armed Forces Institute of Pathology in Washington, DC. These collections include, besides the Michigan State University Collection, the Welker Collection from the University of Wisconsin, the Yakovlev-Haleem Collection from Harvard University, the Meyer Collection from the Johns Hopkins University, and the Huber-Crosby and Crosby-Lauer Collections from the University of Michigan and the C.U. Ariëns Kappers brain collection from Amsterdam Netherlands.Introducing online atlases of the brains of humans, sheep, dolphins, and other animals. A world resource for illustrations of whole brains and stained sections from a great variety of mammals
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.
<<!! checked 20.03.2017 SumsDB was offline; for more information see https://www.researchgate.net/project/salvaging-data-from-sumsdb!! >> SumsDB (the Surface Management System DataBase) is a repository of brain-mapping data (surfaces & volumes; structural & functional data) from many laboratories.
>>> !!!!! The Cell Centered Database is no longer on serice. It has been merged with "Cell image library": https://www.re3data.org/repository/r3d100000023 !!!!! <<<<
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.