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Found 8 result(s)
This website makes data available from the first round of data sharing projects that were supported by the CRCNS funding program. To enable concerted efforts in understanding the brain experimental data and other resources such as stimuli and analysis tools should be widely shared by researchers all over the world. To serve this purpose, this website provides a marketplace and discussion forum for sharing tools and data in neuroscience. To date we host experimental data sets of high quality that will be valuable for testing computational models of the brain and new analysis methods. The data include physiological recordings from sensory and memory systems, as well as eye movement data.
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 PRO-ACT platform houses the largest ALS clinical trials dataset ever created. It is a powerful tool for biomedical researchers, statisticians, clinicians, or anyone else interested in "Big Data." PRO-ACT merges data from existing public and private clinical trials, generating an invaluable resource for the design of future ALS clinical trials. The database will also contribute to the identification of unique observations, novel correlations, and patterns of ALS disease progression, as well as a variety of still unconsidered analyses. More than 600,000 people around them world are battling ALS. The disease strikes indiscriminately, and typically patients will die within 2-5 years following diagnosis. Currently, there are no effective treatments or a cure for ALS. Users of PRO-ACT are helping to accelerate the discovery, development, and delivery of ALS treatments, which will provide hope to patients and their families.
LifeMap Discovery® is a compendium of embryonic development for stem cell research and regenerative medicine, constructed by integrating extensive molecular, cellular, anatomical and medical data curated from scientific literature and high-throughput data sources.
The main goal of the CLUES-project is to provide constrained simulations of the local universe designed to be used as a numerical laboratory of the current paradigm. The simulations will be used for unprecedented analysis of the complex dark matter and gasdynamical processes which govern the formation of galaxies. The predictions of these experiments can be easily compared with the detailed observations of our galactic neighborhood. Some of the CLUES data is now publicly available via the CosmoSim database (https://www.cosmosim.org/). This includes AHF halo catalogues from the Box 64, WMAP3 resimulations of the Local Group with 40963 particle resolution.
PathCards is an integrated database of human biological pathways and their annotations. Human pathways were clustered into SuperPaths based on gene content similarity. Each PathCard provides information on one SuperPath which represents one or more human pathways.
Country
The Cross-National Time-Series Data Archive (CNTS) was initiated by Arthur S. Banks in 1968 with the aim of assembling, in machine readable, longitudinal format, certain of the aggregate data resources of The Statesman’s Yearbook. The CNTS offers a listing of international and national country-data facts. The dataset contains statistical information on a range of countries, with data entries ranging from 1815 to the present.
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.