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Found 60 result(s)
Pubchem contains 3 databases. 1. PubChem BioAssay: The PubChem BioAssay Database contains bioactivity screens of chemical substances described in PubChem Substance. It provides searchable descriptions of each bioassay, including descriptions of the conditions and readouts specific to that screening procedure. 2. PubChem Compound: The PubChem Compound Database contains validated chemical depiction information provided to describe substances in PubChem Substance. Structures stored within PubChem Compounds are pre-clustered and cross-referenced by identity and similarity groups. 3. PubChem Substance. The PubChem Substance Database contains descriptions of samples, from a variety of sources, and links to biological screening results that are available in PubChem BioAssay. If the chemical contents of a sample are known, the description includes links to PubChem Compound.
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The World Atlas of Language Structures (WALS) is a large database of structural (phonological, grammatical, lexical) properties of languages gathered from descriptive materials (such as reference grammars) by a team of 55 authors (many of them the leading authorities on the subject).
The Data Catalogue is a service that allows University of Liverpool Researchers to create records of information about their finalised research data, and save those data in a secure online environment. The Data Catalogue provides a good means of making that data available in a structured way, in a form that can be discovered by both general search engines and academic search tools. There are two types of record that can be created in the Data Catalogue: A discovery-only record – in these cases, the research data may be held somewhere else but a record is provided to help people find it. A record is created that alerts users to the existence of the data, and provides a link to where those data are held. A discovery and data record – in these cases, a record is created to help people discover the data exist, and the data themselves are deposited into the Data Catalogue. This process creates a unique Digital Object identifier (DOI) which can be used in citations to the data.
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It's a multidisciplinary repository that collect and diseminate research, academic, institutional and learning results from Universitat Jaume I. It also includes digitised documentary material on the province of CastellĂł and other information resources from different institutions, like Spain-European Union Digital Archive (SEDAS).
The Research Collection is ETH Zurich's publication platform. It unites the functions of a university bibliography, an open access repository and a research data repository within one platform. Researchers who are affiliated with ETH Zurich, the Swiss Federal Institute of Technology, may deposit research data from all domains. They can publish data as a standalone publication, publish it as supplementary material for an article, dissertation or another text, share it with colleagues or a research group, or deposit it for archiving purposes. Research-data-specific features include flexible access rights settings, DOI registration and a DOI preview workflow, content previews for zip- and tar-containers, as well as download statistics and altmetrics for published data. All data uploaded to the Research Collection are also transferred to the ETH Data Archive, ETH Zurich’s long-term archive.
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UQ eSpace is the single authoritative source for the research outputs of the staff and students of the University of Queensland and is the archival home of UQ Research Higher Degree digital theses. UQ eSpace raises the visibility and accessibility of UQ publications to the wider world and provides data for mandatory Government reporting requirements such as the Higher Education Research Data Collection (HERDC) and Excellence in Research for Australia (ERA) as well as for the internal UQ systems such as the Q-Index. It also operates as an institutional repository for open access publications, research datasets and other digitised materials created by staff of the University such as print materials, photographs, audio materials, videos, manuscripts and other original works.
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.
ePrints Soton is the University's Research Repository. It contains journal articles, books, PhD theses, conference papers, data, reports, working papers, art exhibitions and more. Where possible, journal articles, conference proceedings and research data made open access.
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Open At LaTrobe (OPAL) is La Trobe University’s official repository for Open Access materials generated by academic and professional staff and HDR students. These include publications and other research outputs, theses, open data, and educational resources. OPAL enables the storage, sharing, and selective publication of files and the assignment of a persistent DOI. Users maintain control over who can see their private files and all uploads are stored in La Trobe University approved storage. Access is via La Trobe University login credentials. La Trobe produces a wide range of useful datasets including supplementary data associated with publications and stand-alone datasets and collections.
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.
IntEnz contains the recommendation of the Nomenclature Committee of the International Union of Biochemistry and Molecular Biology on the nomenclature and classification of enzyme-catalyzed reactions. Users can browse by enzyme classification or use advanced search options to search enzymes by class, subclass and sub-subclass information.
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jPOSTrepo (Japan ProteOme STandard Repository) is a repository of sharing MS raw/processed data. It consists of a high-speed file upload process, flexible file management system and easy-to-use interfaces. Users can release their "raw/processed" data via this site with a unique identifier number for the paper publication. Users also can suspend (or "embargo") their data until their paper is published. The file transfer from users’ computer to our repository server is very fast (roughly ten times faster than usual file transfer) and uses only web browsers – it does not require installing any additional software.
The UBIRA eData repository is a multidisciplinary online service for the registration, preservation and publication of research datasets produced or collected at the University of Birmingham. It is part of the University of Birmingham Research Archive (UBIRA).
The WashU Research Data repository accepts any publishable research data set, including textual, tabular, geospatial, imagery, computer code, or 3D data files, from researchers affiliated with Washington University in St. Louis. Datasets include metadata and are curated and assigned a DOI to align with FAIR data principles.
Open access repository for digital research created at the University of Minnesota. U of M researchers may deposit data to the Libraries’ Data Repository for U of M (DRUM), subject to our collection policies. All data is publicly accessible. Data sets submitted to the Data Repository are reviewed by data curation staff to ensure that data is in a format and structure that best facilitates long-term access, discovery, and reuse.
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DataverseNO (https://dataverse.no) is a curated, FAIR-aligned national generic repository for open research data from all academic disciplines. DataverseNO commits to facilitate that published data remain accessible and (re)usable in a long-term perspective. The repository is owned and operated by UiT The Arctic University of Norway. DataverseNO accepts submissions from researchers primarily from Norwegian research institutions. Datasets in DataverseNO are grouped into institutional collections as well as special collections. The technical infrastructure of the repository is based on the open source application Dataverse (https://dataverse.org), which is developed by an international developer and user community led by Harvard University.
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.
eLaborate is an online work environment in which scholars can upload scans, transcribe and annotate text, and publish the results as on online text edition which is freely available to all users. Short information about and a link to already published editions is presented on the page Editions under Published. Information about editions currently being prepared is posted on the page Ongoing projects. The eLaborate work environment for the creation and publication of online digital editions is developed by the Huygens Institute for the History of the Netherlands of the Royal Netherlands Academy of Arts and Sciences. Although the institute considers itself primarily a research facility and does not maintain a public collection profile, Huygens ING actively maintains almost 200 digitally available resource collections.
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Swedish National Data Service (SND) is a research data infrastructure designed to assist researchers in preserving, maintaining, and disseminating research data in a secure and sustainable manner. The SND Search function makes it easy to find, use, and cite research data from a variety of scientific disciplines. Together with an extensive network of almost 40 Swedish higher education institutions and other research organisations, SND works for increased access to research data, nationally as well as internationally.
The HomoloGene database provides a system for the automated detection of homologs among annotated genes of genomes across multiple species. These homologs are fully documented and organized by homology group. HomoloGene processing uses proteins from input organisms to compare and sequence homologs, mapping back to corresponding DNA sequences.