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Found 36 result(s)
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The Institutional repository collects, disseminates and preserves in digital form, the intellectual output that results from the academic and research activity of the Universitat Pompeu Fabra (UPF). Its Purpose is to Increase the impact of research done at the UPF and STIs intellectual memory.
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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.
The UniProt Knowledgebase (UniProtKB) is the central hub for the collection of functional information on proteins, with accurate, consistent and rich annotation. In addition to capturing the core data mandatory for each UniProtKB entry (mainly, the amino acid sequence, protein name or description, taxonomic data and citation information), as much annotation information as possible is added. This includes widely accepted biological ontologies, classifications and cross-references, and clear indications of the quality of annotation in the form of evidence attribution of experimental and computational data. The Universal Protein Resource (UniProt) is a comprehensive resource for protein sequence and annotation data. The UniProt databases are the UniProt Knowledgebase (UniProtKB), the UniProt Reference Clusters (UniRef), and the UniProt Archive (UniParc). The UniProt Metagenomic and Environmental Sequences (UniMES) database is a repository specifically developed for metagenomic and environmental data. The UniProt Knowledgebase,is an expertly and richly curated protein database, consisting of two sections called UniProtKB/Swiss-Prot and UniProtKB/TrEMBL.
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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Morph·D·Base has been developed to serve scientific research and education. It provides a platform for storing the detailed documentation of all material, methods, procedures, and concepts applied, together with the specific parameters, values, techniques, and instruments used during morphological data production. In other words, it's purpose is to provide a publicly available resource for recording and documenting morphological metadata. Moreover, it is also a repository for different types of media files that can be uploaded in order to serve as support and empirical substantiation of the results of morphological investigations. Our long-term perspective with Morph·D·Base is to provide an instrument that will enable a highly formalized and standardized way of generating morphological descriptions using a morphological ontology that will be based on the web ontology language (OWL - http://www.w3.org/TR/owl-features/). This, however, represents a project that is still in development.
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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.
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.
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.
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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.
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.
Reference anatomies of the brain and corresponding atlases play a central role in experimental neuroimaging workflows and are the foundation for reporting standardized results. The choice of such references —i.e., templates— and atlases is one relevant source of methodological variability across studies, which has recently been brought to attention as an important challenge to reproducibility in neuroscience. TemplateFlow is a publicly available framework for human and nonhuman brain models. The framework combines an open database with software for access, management, and vetting, allowing scientists to distribute their resources under FAIR —findable, accessible, interoperable, reusable— principles. TemplateFlow supports a multifaceted insight into brains across species, and enables multiverse analyses testing whether results generalize across standard references, scales, and in the long term, species, thereby contributing to increasing the reliability of neuroimaging results.
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The National Genomics Data Center (NGDC), part of the China National Center for Bioinformation (CNCB), advances life & health sciences by providing open access to a suite of resources, with the aim to translate big data into big discoveries and support worldwide activities in both academia and industry.
BrainMaps.org, launched in May 2005, is an interactive multiresolution next-generation brain atlas that is based on over 20 million megapixels of sub-micron resolution, annotated, scanned images of serial sections of both primate and non-primate brains and that is integrated with a high-speed database for querying and retrieving data about brain structure and function over the internet. Currently featured are complete brain atlas datasets for various species, including Macaca mulatta, Chlorocebus aethiops, Felis catus, Mus musculus, Rattus norvegicus, and Tyto alba.
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BRENDA is the main collection of enzyme functional data available to the scientific community worldwide. The enzymes are classified according to the Enzyme Commission list of enzymes. It is available free of charge for via the internet (http://www.brenda-enzymes.org/) and as an in-house database for commercial users (requests to our distributor Biobase). The enzymes are classified according to the Enzyme Commission list of enzymes. Some 5000 "different" enzymes are covered. Frequently enzymes with very different properties are included under the same EC number. BRENDA includes biochemical and molecular information on classification, nomenclature, reaction, specificity, functional parameters, occurrence, enzyme structure, application, engineering, stability, disease, isolation, and preparation. The database also provides additional information on ligands, which function as natural or in vitro substrates/products, inhibitors, activating compounds, cofactors, bound metals, and other attributes.
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Sikt archives research data on people and society to make sure the data can be shared and is made available for reuse. We continuously enrich our data collections to provide a richer basis for research. Sikt’s main focus is quantitative data matrices on individuals, organisations, administrative, political, and geographical actors. The archive specialise in survey data, which undergoes extensive curation at the variable level and detailed metadata is produced and published in Norwegian and English.
MassBank of North America (MoNA) is a metadata-centric, auto-curating repository designed for efficient storage and querying of mass spectral records. It intends to serve as a the framework for a centralized, collaborative database of metabolite mass spectra, metadata and associated compounds. MoNA currently contains over 200,000 mass spectral records from experimental and in-silico libraries as well as from user contributions.
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.
InnateDB is a publicly available database of the genes, proteins, experimentally-verified interactions and signaling pathways involved in the innate immune response of humans, mice and bovines to microbial infection. The database captures an improved coverage of the innate immunity interactome by integrating known interactions and pathways from major public databases together with manually-curated data into a centralised resource. The database can be mined as a knowledgebase or used with our integrated bioinformatics and visualization tools for the systems level analysis of the innate immune response.
The OpenNeuro project (formerly known as the OpenfMRI project) was established in 2010 to provide a resource for researchers interested in making their neuroimaging data openly available to the research community. It is managed by Russ Poldrack and Chris Gorgolewski of the Center for Reproducible Neuroscience at Stanford University. The project has been developed with funding from the National Science Foundation, National Institute of Drug Abuse, and the Laura and John Arnold Foundation.
PDBj (Protein Data Bank Japan) provides a centralized PDB archive of macromolecular structures, integrated tools for data retrieval, visualization, and functional characterization. PDBj is supported by JST-NBDC and Osaka University.