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Found 61 result(s)
caNanoLab is a data sharing portal designed to facilitate information sharing in the biomedical nanotechnology research community to expedite and validate the use of nanotechnology in biomedicine. caNanoLab provides support for the annotation of nanomaterials with characterizations resulting from physico-chemical and in vitro assays and the sharing of these characterizations and associated nanotechnology protocols in a secure fashion.
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The RAMEDIS system is a platform independent, web-based information system for rare metabolic diseases based on filed case reports. It was developed in close cooperation with clinical partners to allow them to collect information on rare metabolic diseases with extensive details, e.g. about occurring symptoms, laboratory findings, therapy and molecular data.
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AURIN is a collaborative national network of leading researchers and data providers across the academic, government, and private sectors. We provide a one-stop online workbench with access to thousands of multidisciplinary datasets, from over 100 different data sources.
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The Maelstrom Catalogue provides a user-friendly solution for data discovery. It contains comprehensive information about epidemiological research networks and studies, and the data they have collected. It also provides information about harmonized data generated by these research networks.
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BCCM/IHEM is a fungal culture collection specialized in medical and veterinary mycology. About 16.000 strains of yeasts and moulds are available from all over the world: pathogens, allergenic species, strains producing mycotoxins, reference strains, teaching material, etc. It also comprises the Raymond Vanbreuseghem collection and the collection of Janssen Pharmaceutica. The BCCM/IHEM collection makes strains or their genomic DNA publicly available for medical, pharmaceutical and biological research, as well as for method validation, testing or educational purposes. Deposits of strains for public access are free of charge for the depositor. The collection also accept safe and patent deposits, and offers a range of services including trainings in mycology and identifications of strains. Moreover, BCCM/IHEM has expertise in fungal taxonomy, in MALDI-TOF MS identification of moulds and yeasts as well as in genomics (whole genome sequencing of fungal strains, phylogenomics, phylogenetics).
All ADNI data are shared without embargo through the LONI Image and Data Archive (IDA), a secure research data repository. Interested scientists may obtain access to ADNI imaging, clinical, genomic, and biomarker data for the purposes of scientific investigation, teaching, or planning clinical research studies. "The Alzheimer’s Disease Neuroimaging Initiative (ADNI) unites researchers with study data as they work to define the progression of Alzheimer’s disease (AD). ADNI researchers collect, validate and utilize data, including MRI and PET images, genetics, cognitive tests, CSF and blood biomarkers as predictors of the disease. Study resources and data from the North American ADNI study are available through this website, including Alzheimer’s disease patients, mild cognitive impairment subjects, and elderly controls. "
WFCC Global Catalogue of Microorganisms (GCM) is expected to be a robust, reliable and user-friendly system to help culture collections to manage, disseminate and share the information related to their holdings. It also provides a uniform interface for the scientific and industrial communities to access the comprehensive microbial resource information.
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.
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BCCM/MUCL is a generalist fungal culture collection of over 30000 filamentous fungi, yeasts and arbuscular mycorrhizal fungi including type, reference and test strains. It provides curated documentation and information on these bioresourced in its database. The collections activities include the distribution of its holdings, the accession of new material in its public, safe and patent domains, and services valorising its holdings and/or expertise to cultivate, isolate and identify fungal diversity in natural and anthropological ecosystems, agro-food (food and feed transformation and spoilage), and fungal-plant interactions.
NeuGRID is a secure data archiving and HPC processing system. The neuGRID platform uses a robust infrastructure to provide researchers with a simple interface for analysing, searching, retrieving and disseminating their biomedical data. With hundreds of investigators across the globe and more than 10 million of downloadable attributes, neuGRID aims to become a widespread resource for brain analyses. NeuGRID platform guarantees reliability with a fault-tolerant network to prevent system failure.
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NIE Data Repository is the institutional research data repository for National Institute of Education, Nanyang Technological University (NIE NTU), Singapore. The Repository is open to NIE researchers and staff to archive, publish and share their final research data related to publications.
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.
The ABCD Data Repository houses all data generated by the Adolescent Brain Cognitive Development (ABCD) Study. The ABCD Study is supported by NIH partners (the National Institute on Drug Abuse, the National Institute on Alcohol Abuse and Alcoholism, the National Cancer Institute, the Eunice Kennedy Shriver National Institute of Child Health and Human Development, the National Institute of Mental Health, the National Institute on Minority Health and Health Disparities, the National Institute of Neurological Disorders and Stroke, the NIH Office of Behavioral and Social Sciences Research, and the NIH Office of Research on Women’s Health), as well as the Centers for Disease Control and Prevention – Division of Adolescent and School Health. This repository will store data generated by ABCD investigators, serve as a collaborative platform for harmonizing these data, and share those data with qualified researchers.
The MG-RAST server is an open source system for annotation and comparative analysis of metagenomes. Users can upload raw sequence data in fasta format; the sequences will be normalized and processed and summaries automatically generated. The server provides several methods to access the different data types, including phylogenetic and metabolic reconstructions, and the ability to compare the metabolism and annotations of one or more metagenomes and genomes. In addition, the server offers a comprehensive search capability. Access to the data is password protected, and all data generated by the automated pipeline is available for download in a variety of common formats. MG-RAST has become an unofficial repository for metagenomic data, providing a means to make your data public so that it is available for download and viewing of the analysis without registration, as well as a static link that you can use in publications. It also requires that you include experimental metadata about your sample when it is made public to increase the usefulness to the community.
Gemma is a database for the meta-analysis, re-use and sharing of genomics data, currently primarily targeted at the analysis of gene expression profiles. Gemma contains data from thousands of public studies, referencing thousands of published papers. Users can search, access and visualize co-expression and differential expression results.
STOREDB is a platform for the archiving and sharing of primary data and outputs of all kinds, including epidemiological and experimental data, from research on the effects of radiation. It also provides a directory of bioresources and databases containing information and materials that investigators are willing to share. STORE supports the creation of a radiation research commons.
The COVID-19 Data Portal was launched in April 2020 to bring together relevant datasets for sharing and analysis in an effort to accelerate coronavirus research. It enables researchers to upload, access and analyse COVID-19 related reference data and specialist datasets as part of the wider European COVID-19 Data Platform.
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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.
ASAP (a systematic annotation package for community analysis of genomes) is a relational database and web interface developed to store, update and distribute genome sequence data and gene expression data collected by or in collaboration with researchers at the University of Wisconsin - Madison. ASAP was designed to facilitate ongoing community annotation of genomes and to grow with genome projects as they move from the preliminary data stage through post-sequencing functional analysis. The ASAP database includes multiple genome sequences at various stages of analysis, and gene expression data from preliminary experiments.
CalSurv is a comprehensive information on West Nile virus, plague, malaria, Lyme disease, trench fever and other vectorborne diseases in California — where they are, where they’ve been, where they may be headed and what new diseases may be emerging.The CalSurv Web site serves as a portal or a single interface to all surveillance-related Web sites in California.
The Avian Knowledge Network (AKN) is an international network of governmental and non-governmental institutions and individuals linking avian conservation, monitoring and science through efficient data management and coordinated development of useful solutions using best-science practices based on the data.
Content type(s)
A machine learning data repository with interactive visual analytic techniques. This project is the first to combine the notion of a data repository with real-time visual analytics for interactive data mining and exploratory analysis on the web. State-of-the-art statistical techniques are combined with real-time data visualization giving the ability for researchers to seamlessly find, explore, understand, and discover key insights in a large number of public donated data sets. This large comprehensive collection of data is useful for making significant research findings as well as benchmark data sets for a wide variety of applications and domains and includes relational, attributed, heterogeneous, streaming, spatial, and time series data as well as non-relational machine learning data. All data sets are easily downloaded into a standard consistent format. We also have built a multi-level interactive visual analytics engine that allows users to visualize and interactively explore the data in a free-flowing manner.