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This Animal Quantitative Trait Loci (QTL) database (Animal QTLdb) is designed to house all publicly available QTL and trait mapping data (i.e. trait and genome location association data; collectively called "QTL data" on this site) on livestock animal species for easily locating and making comparisons within and between species. New database tools are continuely added to align the QTL and association data to other types of genome information, such as annotated genes, RH / SNP markers, and human genome maps. Besides the QTL data from species listed below, the QTLdb is open to house QTL/association date from other animal species where feasible. Note that the JAS along with other journals, now require that new QTL/association data be entered into a QTL database as part of their publication requirements.
CDC.gov is the Centers for Disease Control and Prevention primary online communication channel. CDC.gov provides users with credible, reliable health information on Data and Statistics, Diseases and Conditions, Emergencies and Disasters, Environmental Health, Healthy Living, Injury, Violence and Safety,Life Stages and Populations, Travelers' Health, Workplace Safety and Health
The SAR Data Center has a large data archive of Synthetic Aperture Radar (SAR) from a variety of sensors available at no cost. Much of the SAR data in the ASF SDC archive is limited in distribution to the scientific research community and U.S. Government Agencies. In accordance with the Memoranda of Understanding (MOU) between the relevant flight agencies (CSA, ESA, JAXA) and the U.S. State Department, the ASF SDC does not distribute SAR data for commercial use. The research community can access the data (ERS-1, ERS-2, JERS-1, RADARSAT-1, and ALOS PALSAR) via a brief proposal process.
The Database explores the interactions of chemicals and proteins. It integrates information about interactions from metabolic pathways, crystal structures, binding experiments and drug-target relationships. Inferred information from phenotypic effects, text mining and chemical structure similarity is used to predict relations between chemicals. STITCH further allows exploring the network of chemical relations, also in the context of associated binding proteins.