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Found 9 result(s)
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ScholarBank@NUS is the university's Institutional Repository (IR). Its goals are to collect, preserve and showcase the research output including research data of NUS researchers and departments.
Country
The AMUReD Institutional Research Data Repository of the Adam Mickiewicz University in Poznan (UAM) collects and provides access to digital versions of research data collected, processed or produced as part of the scientific research or developmental work of UAM employees.The AMUReD Repository is part of the AMU Research Portal, with University Library in Poznan as the operating unit. Depositing data is possible after logging into the AMU Research Portal, according to the attached instructions. The AMUReD repository is open, and research data are made available in three models: open (Open Access), embargo (Embargo) and closed (Restricted Access). The detailed rules of the AMUReD repository are defined in the Regulations. The AMUReD repository complies with the FAIR Principles. Each dataset is given a unique DOI identifier. The AMUReD repository complies with the FAIR Principles. Each dataset is given a unique DOI identifier. The prefix for DOIs is doi:10.60629. It is possible to choose a Creative Commons license for shared datasets.
The Catalogue of Life is the most comprehensive and authoritative global index of species currently available. It consists of a single integrated species checklist and taxonomic hierarchy. The Catalogue holds essential information on the names, relationships and distributions of over 1.8 million species. This figure continues to rise as information is compiled from diverse sources around the world.
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The Australian Antarctic Data Centre (AADC) provides data collection and data management services in Australia's Antarctic Science Program. The AADC manages science data from Australia's Antarctic research, maps Australia's areas of interest in the Antarctic region, manages Australia's Antarctic state of the environment reporting, and provides advice and education and a range of other products.
PSnpBind is a large database of protein–ligand complexes covering a wide range of binding pocket mutations and small molecules’ landscape. This database can be used as a source of data for different types of studies, for example, developing machine learning algorithms to predict protein–ligand affinity or mutation's effect on it which requires an extensive amount of data with a wide coverage of mutation types and small molecules. Also, studies of protein-ligand interactions and conformer orientation changes across different mutated versions of a protein can be established using data from PSnpBind.