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Found 27 result(s)
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The JenAge Ageing Factor Database AgeFactDB is aimed at the collection and integration of ageing phenotype and lifespan data. Ageing factors are genes, chemical compounds or other factors such as dietary restriction, for example. In a first step ageing-related data are primarily taken from existing databases. In addition, new ageing-related information is included both by manual and automatic information extraction from the scientific literature. Based on a homology analysis, AgeFactDB also includes genes that are homologous to known ageing-related genes. These homologs are considered as candidate or putative ageing-related genes.
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
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<<<!!!<<< This repository is no longer available. >>>!!!>>> A human interactome map. The sequencing of the human genome has provided a surprisingly small number of genes, indicating that the complex organization of life is not reflected in the gene number but, rather, in the gene products – that is, in the proteins. These macromolecules regulate the vast majority of cellular processes by their ability to communicate with each other and to assemble into larger functional units. Therefore, the systematic analysis of protein-protein interactions is fundamental for the understanding of protein function, cellular processes and, ultimately, the complexity of life. Moreover, interactome maps are particularly needed to link new proteins to disease pathways and the identification of novel drug targets.
EBRAINS offers one of the most comprehensive platforms for sharing brain research data ranging in type as well as spatial and temporal scale. We provide the guidance and tools needed to overcome the hurdles associated with sharing data. The EBRAINS data curation service ensures that your dataset will be shared with maximum impact, visibility, reusability, and longevity, hhttps://www.ebrains.eu/data/find-data/. Find data - the user interface of the EBRAINS Knowledge Graph - allows you to easily find data of interest. EBRAINS hosts a wide range of data types and models from different species. All data are well described and can be accessed immediately for further analysis.
A place where researchers can publicly store and share unthresholded statistical maps, parcellations, and atlases produced by MRI and PET studies.
The US BRAIN Initiative archive for publishing and sharing neurophysiology data including electrophysiology, optophysiology, and behavioral time-series, and images from immunostaining experiments.
Welcome to the GALENOS Data Repository. The GALENOS Data Repository provides access to all the research data produced by the Global Alliance for Living Evidence on aNxiety, depressiOn and pSychosis (GALENOS). If you're interested in learning more about GALENOS, please visit the website at https://galenos.org.uk.
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The Austrian NeuroCloud (ANC) is a FAIR-enabling platform for sustainable research data management in Cognitive Neuroscience. Most of the offered research data is restricted, the publicly available datasets can be seen under https://data.anc.plus.ac.at/explore The ANC offers tools and services to archive, manage, and share neurocognitive data flexibly and according to community standards. Scientists have full control over what they share (e.g., full original datasets or data derivatives), how they share it (by choosing from a selection of licensing models), and with whom (e.g., by using the ANC’s adjustable User Agreement templates). The ANC provides persistent DOIs for data releases and operates in accordance with European GDPR. Moreover, the ANC fully supports the mission of the EOSC and is committed to the EU’s open science policy, legal standards, and best open science practices. Accordingly, the ANC aspires to facilitate FAIR data operations along the entire data lifecycle, actively supporting the ongoing shift in research culture towards increased transparency, data reusability, and result reproducibility.
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The ICES Data Repository consists of record-level, coded and linkable health data sets. It encompasses much of the publicly funded administrative health services records for the Ontario population eligible for universal health coverage since 1986 and is capable of integrating research-specific data, registries and surveys. Currently, the repository includes health service records for as many as 13 million people. Files in the ICES Data Repository are described in the Data Dictionary. This includes ICES General Use Data, as well as ICES Controlled Use Data. Datasets obtained by ICES for specific project(s) (project-specific data) are not described in the Data Dictionary. The ICES Data Dictionary is an essential resource for anyone doing research at ICES. The information in this Data Dictionary is almost entirely based on the metadata belonging to the datasets described.
The CONP portal is a web interface for the Canadian Open Neuroscience Platform (CONP) to facilitate open science in the neuroscience community. CONP simplifies global researcher access and sharing of datasets and tools. The portal internalizes the cycle of a typical research project: starting with data acquisition, followed by processing using already existing/published tools, and ultimately publication of the obtained results including a link to the original dataset. From more information on CONP, please visit https://conp.ca
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.
The Pennsieve platform is a cloud-based scientific data management platform focused on integrating complex datasets, fostering collaboration and publishing scientific data according to all FAIR principles of data sharing. The platform is developed to enable individual labs, consortiums, or inter-institutional projects to manage, share and curate data in a secure cloud-based environment and to integrate complex metadata associated with scientific files into a high-quality interconnected data ecosystem. The platform is used as the backend for a number of public repositories including the NIH SPARC Portal and Pennsieve Discover repositories. It supports flexible metadata schemas and a large number of scientific file-formats and modalities.
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An Open Science resource that promotes scientific research and discovery in neurological diseases and accelerates the development of new treatments. It includes a growing collection of biospecimens, longitudinal clinical and neuropsychiatric information, imaging and genetic data from patients with neurological disease as well as healthy controls.
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The CHILDdb platform provides access to data produced by the CHILD project, a longitudinal birth cohort study of children from pregnancy to 8 years of age, across four Canadian provinces. This study analyzes the participants' home environment including physical, chemical, viral, bacterial, nutritional and psychosocial exposures. This data is expected to further knowledge of the genetic and environmental determinants of atopic diseases including asthma, allergy, allergic rhinitis, and eczema. Researchers can create an account to view meta and aggregate data; access demographic data summaries based on selected variables; and submit a scientific Concept Proposal for approval to access individual-level study data.
INDI was formed as a next generation FCP effort. INDI aims to provide a model for the broader imaging community while simultaneously creating a public dataset capable of dwarfing those that most groups could obtain individually.
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SISSA Open Data is the Sissa repository for the research data managment. It is an institutional repository that captures, stores, preserves, and redistributes the data of the SISSA scientific community in digital form. SISSA Open Data is managed by the SISSA Library as a service to the SISSA scientific community.
SimTK is a free project-hosting platform for the biomedical computation community that enables researchers to easily share their software, data, and models and provides the infrastructure so they can support and grow a community around their projects. It has over 126.656 members, hosts 1.648 projects from researchers around the world, and has had more than 2.095.783 files downloaded from it. Individuals have created SimTK projects to meet publisher and funding agencies’ software and data sharing requirements, run scientific challenges, create a collection of their community’s resources, and much more.
!!! >>> merged with https://www.re3data.org/repository/r3d100012653 <<< !!! 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.
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The Data Access Support Hub (DASH) is a one-stop data access service portal for researchers requiring multi-regional data in Canada. DASH services are provided by a multi-centre coordination team from various provincial/territorial data centres and pan-Canadian organizations, including the Canadian Institute for Health Information (CIHI) and Statistics Canada.
OASIS-3 is the latest release in the Open Access Series of Imaging Studies (OASIS) that aimed at making neuroimaging datasets freely available to the scientific community. By compiling and freely distributing this multi-modal dataset, we hope to facilitate future discoveries in basic and clinical neuroscience. Previously released data for OASIS-Cross-sectional (Marcus et al, 2007) and OASIS-Longitudinal (Marcus et al, 2010) have been utilized for hypothesis driven data analyses, development of neuroanatomical atlases, and development of segmentation algorithms. OASIS-3 is a longitudinal neuroimaging, clinical, cognitive, and biomarker dataset for normal aging and Alzheimer’s Disease. The OASIS datasets hosted by central.xnat.org provide the community with open access to a significant database of neuroimaging and processed imaging data across a broad demographic, cognitive, and genetic spectrum an easily accessible platform for use in neuroimaging, clinical, and cognitive research on normal aging and cognitive decline. All data is available via www.oasis-brains.org.
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.