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The Health Data Research Innovation Gateway (the ‘Gateway’) provides a common entry point to discover and enquire about access to UK health datasets for research and innovation. It provides detailed information about the datasets, which are held by members of the UK Health Data Research Alliance, such as a description, size of the population, and the legal basis for access. The Gateway includes the ability to search for research projects, publications and health data tools, such as those related to COVID-19. New interactive features provide a community forum for researchers to collaborate and connect and the ability to add research projects. The Innovation Gateway does not hold or store any datasets or patient or health data but rather acts as a portal to allow discovery of datasets and to request access to them for health research. A dataset is a collection of related individual pieces of data but in the case of health data, identifiable information (e.g. name or NHS number) is removed and data is de-identified where possible. When you access the Gateway you will not be able to view or extract the data itself. Instead, you will be able to see information that describes what the different datasets are (e.g. where the dataset has come from, a description of the dataset, the time period and the geographical areas the dataset covers).
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The DrugBank database is a unique bioinformatics and cheminformatics resource that combines detailed drug (i.e. chemical, pharmacological and pharmaceutical) data with comprehensive drug target (i.e. sequence, structure, and pathway) information. The latest release of DrugBank (version 5.1.1, released 2018-07-03) contains 11,881 drug entries including 2,526 approved small molecule drugs, 1,184 approved biotech (protein/peptide) drugs, 129 nutraceuticals and over 5,751 experimental drugs. Additionally, 5,132 non-redundant protein (i.e. drug target/enzyme/transporter/carrier) sequences are linked to these drug entries. Each DrugCard entry contains more than 200 data fields with half of the information being devoted to drug/chemical data and the other half devoted to drug target or protein data.
Earthdata powered by EOSDIS (Earth Observing System Data and Information System) is a key core capability in NASA’s Earth Science Data Systems Program. It provides end-to-end capabilities for managing NASA’s Earth science data from various sources – satellites, aircraft, field measurements, and various other programs. EOSDIS uses the metadata and service discovery tool Earthdata Search https://search.earthdata.nasa.gov/search. The capabilities of EOSDIS constituting the EOSDIS Science Operations are managed by NASA's Earth Science Data and Information System (ESDIS) Project. The capabilities include: generation of higher level (Level 1-4) science data products for several satellite missions; archiving and distribution of data products from Earth observation satellite missions, as well as aircraft and field measurement campaigns. The EOSDIS science operations are performed within a distributed system of many interconnected nodes - Science Investigator-led Processing Systems (SIPS), and distributed, discipline-specific, Earth science Distributed Active Archive Centers (DAACs) with specific responsibilities for production, archiving, and distribution of Earth science data products. The DAACs serve a large and diverse user community by providing capabilities to search and access science data products and specialized services.
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<<<!!!<<< 2019-12-23: the repository is offline >>>!!!>>> Introduction of genome-scale metabolic network: The completion of genome sequencing and subsequent functional annotation for a great number of species enables the reconstruction of genome-scale metabolic networks. These networks, together with in silico network analysis methods such as the constraint based methods (CBM) and graph theory methods, can provide us systems level understanding of cellular metabolism. Further more, they can be applied to many predictions of real biological application such as: gene essentiality analysis, drug target discovery and metabolic engineering
MalaCards is an integrated database of human maladies and their annotations, modeled on the architecture and richness of the popular GeneCards database of human genes. MalaCards mines and merges varied web data sources to generate a computerized web card for each human disease. Each MalaCard contains disease specific prioritized annotative information, as well as links between associated diseases, leveraging the GeneCards relational database, search engine, and GeneDecks set-distillation tool. As proofs of concept of the search/distill/infer pipeline we find expected elucidations, as well as potentially novel ones.
The BioCyc database collection of Pathway/Genome Databases (PGDBs) provides a reference on the genomes and metabolic pathways of thousands of sequenced organisms. BioCyc PGDBs are generated by software that predict the metabolic pathways of completely sequenced organisms, predict which genes code for missing enzymes in metabolic pathways, and predict operons. BioCyc also integrates information from other bioinformatics databases, such as protein feature and Gene Ontology information from UniProt. The BioCyc website provides a suite of software tools for database searching and visualization, for omics data analysis, and for comparative genomics and comparative pathway questions. From 2016 on, access to the EcoCyc and MetaCyc databases will remain free. Subscriptions to the other 7,600 BioCyc databases will be available to institutions (e.g., libraries), and to individuals. Access to licensed databases via: https://biocyc.org/Product-summary.shtml.