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Found 9 result(s)
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SIDER contains information on marketed medicines and their recorded adverse drug reactions. The information is extracted from public documents and package inserts. The available information include side effect frequency, drug and side effect classifications as well as links to further information, for example drug–target relations.
ICD serves as the international standard for diagnostic classification for all general epidemiological, many health management purposes and clinical use. The ICD's resources include the analysis of different population groups' general health situations, monitoring of the incidence and prevalence of diseases in relation to the characteristics of the individuals affected, reimbursement, resource allocation, quality, and guidelines. The records provide the basis for the compilation of national mortality and morbidity statistics, and enable the storage and retrieval of diagnostic information for clinical epidemiological and quality purposes.
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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.
<<<!!!<<< As of June 30, 2017, HardinMD has been retired, although it is still findable through the WayBack Machine >>>!!!>>>
GeneCards is a searchable, integrative database that provides comprehensive, user-friendly information on all annotated and predicted human genes. It automatically integrates gene-centric data from ~125 web sources, including genomic, transcriptomic, proteomic, genetic, clinical and functional information.
The Africa Health Research Institute (AHRI) has published its updated analytical datasets for 2016. The datasets cover socio-economic, education and employment information for individuals and households in AHRI’s population research area in rural northern KwaZulu-Natal. The datasets also include details on the migration patterns of the individuals and households who migrated into and out of the surveillance area as well as data on probable causes of death for individuals who passed away. Data collection for the 2016 individual interviews – which involves a dried blood spot sample being taken – is still in progress, and therefore datasets on HIV status and General Health only go up to 2015 for now. Over the past 16 years researchers have developed an extensive longitudinal database of demographic, social, economic, clinical and laboratory information about people over the age of 15 living in the AHRI population research area. During this time researchers have followed more than 160 000 people, of which 92 000 are still in the programme.
<<<!!!<<< OFFLINE >>>!!!>>> A recent computer security audit has revealed security flaws in the legacy HapMap site that require NCBI to take it down immediately. We regret the inconvenience, but we are required to do this. That said, NCBI was planning to decommission this site in the near future anyway (although not quite so suddenly), as the 1,000 genomes (1KG) project has established itself as a research standard for population genetics and genomics. NCBI has observed a decline in usage of the HapMap dataset and website with its available resources over the past five years and it has come to the end of its useful life. The International HapMap Project is a multi-country effort to identify and catalog genetic similarities and differences in human beings. Using the information in the HapMap, researchers will be able to find genes that affect health, disease, and individual responses to medications and environmental factors. The Project is a collaboration among scientists and funding agencies from Japan, the United Kingdom, Canada, China, Nigeria, and the United States. All of the information generated by the Project will be released into the public domain. The goal of the International HapMap Project is to compare the genetic sequences of different individuals to identify chromosomal regions where genetic variants are shared. By making this information freely available, the Project will help biomedical researchers find genes involved in disease and responses to therapeutic drugs. In the initial phase of the Project, genetic data are being gathered from four populations with African, Asian, and European ancestry. Ongoing interactions with members of these populations are addressing potential ethical issues and providing valuable experience in conducting research with identified populations. Public and private organizations in six countries are participating in the International HapMap Project. Data generated by the Project can be downloaded with minimal constraints. The Project officially started with a meeting in October 2002 (https://www.genome.gov/10005336/) and is expected to take about three years.
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The Toxin and Toxin Target Database is a unique bioinformatics resource that combines detailed toxin data with comprehensive toxin target information. The focus of the T3DB is on providing mechanisms of toxicity and target proteins for each toxin. This dual nature of the T3DB, in which toxin and toxin target records are interactively linked in both directions, makes it unique from existing databases.
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.