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Found 31 result(s)
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GRO.data is a research data repository for the Göttingen Campus. Belonging researchers can use it for free. It serves different purposes such as: to simply preserve datasets, to keep track of changes across several versions, to share data with colleagues, to make data itself publicly available, to receive a persistent identifier upon publications.
As with most biomedical databases, the first step is to identify relevant data from the research community. The Monarch Initiative is focused primarily on phenotype-related resources. We bring in data associated with those phenotypes so that our users can begin to make connections among other biological entities of interest. We import data from a variety of data sources. With many resources integrated into a single database, we can join across the various data sources to produce integrated views. We have started with the big players including ClinVar and OMIM, but are equally interested in boutique databases. You can learn more about the sources of data that populate our system from our data sources page https://monarchinitiative.org/about/sources.
The PLANKTON*NET data provider at the Alfred Wegener Institute for Polar and Marine Research is an open access repository for plankton-related information. It covers all types of phytoplankton and zooplankton from marine and freshwater areas. PLANKTON*NET's greatest strength is its comprehensiveness as for the different taxa image information as well as taxonomic descriptions can be archived. PLANKTON*NET also contains a glossary with accompanying images to illustrate the term definitions. PLANKTON*NET therefore presents a vital tool for the preservation of historic data sets as well as the archival of current research results. Because interoperability with international biodiversity data providers (e.g. GBIF) is one of our aims, the architecture behind the new planktonnet@awi repository is observation centric and allows for mulitple assignment of assets (images, references, animations, etc) to any given observation. In addition, images can be grouped in sets and/or assigned tags to satisfy user-specific needs . Sets (and respective images) of relevance to the scientific community and/or general public have been assigned a persistant digital object identifier (DOI) for the purpose of long-term preservation (e.g. set ""Plankton*Net celebrates 50 years of Roman Treaties"", handle: 10013/de.awi.planktonnet.set.495)"
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The database MORPHYLL contains quantitative and qualitative morphometric data of fossil angiosperm leaves from the Paleogene. The data are compiled from different fossil sites housed in various European Natural History Museums.
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The iBeetle-Base stores gene related information for all genes of the official gene set (red box). Among others, RNA and protein sequences can be downloaded and links lead to the respective annotation in the genome browser. Further, the Drosophila orthologs are displayed including links to FlyBase. Wherever available, the phenotypic data gathered in the iBeetle screen is displayed below the gene information in separate sections for the pupal and larval screening parts (yellow box).
The Virtual Research Environment (VRE) is an open-source data management platform that enables medical researchers to store, process and share data in compliance with the European Union (EU) General Data Protection Regulation (GDPR). The VRE addresses the present lack of digital research data infrastructures fulfilling the need for (a) data protection for sensitive data, (b) capability to process complex data such as radiologic imaging, (c) flexibility for creating own processing workflows, (d) access to high performance computing. The platform promotes FAIR data principles and reduces barriers to biomedical research and innovation. The VRE offers a web portal with graphical and command-line interfaces, segregated data zones and organizational measures for lawful data onboarding, isolated computing environments where large teams can collaboratively process sensitive data privately, analytics workbench tools for processing, analyzing, and visualizing large datasets, automated ingestion of hospital data sources, project-specific data warehouses for structured storage and retrieval, graph databases to capture and query ontology-based metadata, provenance tracking, version control, and support for automated data extraction and indexing. The VRE is based on a modular and extendable state-of-the art cloud computing framework, a RESTful API, open developer meetings, hackathons, and comprehensive documentation for users, developers, and administrators. The VRE with its concerted technical and organizational measures can be adopted by other research communities and thus facilitates the development of a co-evolving interoperable platform ecosystem with an active research community.
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This is an institutional repository which hosts the publications and research outputs (including data sets) of higher and further education institutions in Sachsen-Anhalt, Germany. The interface of the repository is available in German and English. Most of the content is in German.
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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.
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ProteomicsDB started as a protein-centric in-memory database for the exploration of large collections of quantitative mass spectrometry-based proteomics data. The data types and contents grew over time to include RNA-Seq expression data, drug-target interactions and cell line viability data.
This website makes data available from the first round of data sharing projects that were supported by the CRCNS funding program. To enable concerted efforts in understanding the brain experimental data and other resources such as stimuli and analysis tools should be widely shared by researchers all over the world. To serve this purpose, this website provides a marketplace and discussion forum for sharing tools and data in neuroscience. To date we host experimental data sets of high quality that will be valuable for testing computational models of the brain and new analysis methods. The data include physiological recordings from sensory and memory systems, as well as eye movement data.
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The Goethe University Data Repository (GUDe) provides a platform for its members to electronically archive, share, and publish their research data. GUDe is jointly operated by the University Library and the University Data Center of the Goethe University. The metadata of all public content is freely available and indexed by search engines as well as scientific web services. GUDe follows the FAIR principles for long-term accessibility (minimum 10 years), allows for reliable citation via DOIs as well as cooperative access to non-public data and operates on DSpace-CRIS v7. If you have any questions regarding the use of GUDe, please consult the user documentation.
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Thousands of circular RNAs (circRNAs) have recently been shown to be expressed in eukaryotic cells [Salzman et al. 2012, Jeck et al. 2013, Memczak et al. 2013, Salzman et al. 2013]. Here you can explore public circRNA datasets and download the custom python scripts needed to discover circRNAs in your own (ribominus) RNA-seq data.
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The institutional repository Refubium is a service of the University Library of Freie Universität. All the university members (research staff/scientists, students and other authors currently affiliated with Freie Univesität) are encouraged to deposit their scientific papers, master and bachelor thesis, as well as research data.
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HHU ResearchData enables researchers of Heinrich Heine University Düsseldorf to make their research data available to the scientific community.
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The project brings together national key players providing environmentally related biological data and services to develop the ‘German Federation for Biological Data' (GFBio). The overall goal is to provide a sustainable, service oriented, national data infrastructure facilitating data sharing and stimulating data intensive science in the fields of biological and environmental research.
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The Mansfeld's World Database of Agriculture and Horticultural Crops is an online database. As a contribution to the project "Federal Information System on Genetic Resources" (BIG, http://www.big-flora.de/). It reflects the contents of "Mansfeld's Encyclopedia of Agricultural and Horticultural Crops" (Hanelt and IPK 2001) and contains information on 6,100 crop plant species, excluding forestry and ornamental plants. Each species entry provides nomenclature and synonymy, common names in different languages, spontaneous distribution and regions of cultivation, uses, images, references, but also the ancestral species and notes on the phylogeny, variation and history.
The FAIRDOMHub is built upon the SEEK software suite, which is an open source web platform for sharing scientific research assets, processes and outcomes. FAIRDOM (Web Site) will establish a support and service network for European Systems Biology. It will serve projects in standardizing, managing and disseminating data and models in a FAIR manner: Findable, Accessible, Interoperable and Reusable. FAIRDOM is an initiative to develop a community, and establish an internationally sustained Data and Model Management service to the European Systems Biology community. FAIRDOM is a joint action of ERA-Net EraSysAPP and European Research Infrastructure ISBE.
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ResearchGate is a network where 15+ million scientists and researchers worldwide connect to share their work. Researchers can upload data of any type and receive DOIs, detailed statistics and real-time feedback. In Data discovery Section of ResearchGate you can explore the added datasets.
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It is the objective of our motion capture database HDM05 to supply free motion capture data for research purposes. HDM05 contains more than three hours of systematically recorded and well-documented motion capture data in the C3D as well as in the ASF/AMC data format. Furthermore, HDM05 contains for more than 70 motion classes in 10 to 50 realizations executed by various actors.
CottonGen is a new cotton community genomics, genetics and breeding database being developed to enable basic, translational and applied research in cotton. It is being built using the open-source Tripal database infrastructure. CottonGen consolidates and expands the data from CottonDB and the Cotton Marker Database, providing enhanced tools for easy querying, visualizing and downloading research data.