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Found 4 result(s)
Chempound is a new generation repository architecture based on RDF, semantic dictionaries and linked data. It has been developed to hold any type of chemical object expressible in CML and is exemplified by crystallographic experiments and computational chemistry calculations. In both examples, the repository can hold >50k entries which can be searched by SPARQL endpoints and pre-indexing of key fields. The Chempound architecture is general and adaptable to other fields of data-rich science. The Chempound software is hosted at http://bitbucket.org/chempound and is available under the Apache License, Version 2.0
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.
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 ADS is an accredited digital repository for heritage data that supports research, learning and teaching with freely available, high quality and dependable digital resources by preserving and disseminating digital data in the long term. The ADS also promotes good practice in the use of digital data, provides technical advice to the heritage community, and supports the deployment of digital technologies.