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Found 17 result(s)
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<<<!!!<<< This repository is no longer available. >>>!!!>>> A human interactome map. The sequencing of the human genome has provided a surprisingly small number of genes, indicating that the complex organization of life is not reflected in the gene number but, rather, in the gene products – that is, in the proteins. These macromolecules regulate the vast majority of cellular processes by their ability to communicate with each other and to assemble into larger functional units. Therefore, the systematic analysis of protein-protein interactions is fundamental for the understanding of protein function, cellular processes and, ultimately, the complexity of life. Moreover, interactome maps are particularly needed to link new proteins to disease pathways and the identification of novel drug targets.
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The Health Atlas is an alliance of medical ontologists, medical systems biologists and clinical trials groups to design and implement a multi-functional and quality-assured atlas. It provides models, data and metadata on specific use cases from medical research projects from the partner institutions.
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This database host for fungi data related to new classification with morphology, molecular and other important data. This fungal database allows deposition of taxonomic data, phenotypic details and other useful data, which will enhance our current taxonomic understanding and ultimately enable mycologists to gain better and updated insights into the current fungal classification system. In addition, the database will also allow access to comprehensive metadata including descriptions of voucher and type specimens.
The EBiSC Catalogue is a collection of human iPS cells being made available to academic and commercial researchers for use in disease modelling and other forms of preclinical research. The initial collection has been generated from a wide range of donors representing specific disease backgrounds and healthy controls. As the collection grows, more isogenic control lines will become available which will add further to the collection’s appeal.
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Since 2004, the Leibniz Institute for Prevention Research and Epidemiology – BIPS has been working on the establishment and maintenance of the project-based German Pharmacoepidemiological Research Database (short GePaRD). GePaRD is based on claims data from statutory health insurance (SHI) providers and currently includes information on about 20 million persons who have been insured with one of the participating providers since 2004. Per data year, there is information on approximately 17% of the general population from all geographical regions of Germany.
EarthWorks is a discovery tool for geospatial (a.k.a. GIS) data. It allows users to search and browse the GIS collections owned by Stanford University Libraries, as well as data collections from many other institutions. Data can be searched spatially, by manipulating a map; by keyword search; by selecting search limiting facets (e.g., limit to a given format type); or by combining these options.
DEIMS-SDR (Dynamic Ecological Information Management System - Site and dataset registry) is an information management system that allows you to discover long-term ecosystem research sites around the globe, along with the data gathered at those sites and the people and networks associated with them. DEIMS-SDR describes a wide range of sites, providing a wealth of information, including each site’s location, ecosystems, facilities, parameters measured and research themes. It is also possible to access a growing number of datasets and data products associated with the sites. All sites and dataset records can be referenced using unique identifiers that are generated by DEIMS-SDR. It is possible to search for sites via keyword, predefined filters or a map search. By including accurate, up to date information in DEIMS, site managers benefit from greater visibility for their LTER site, LTSER platform and datasets, which can help attract funding to support site investments. The aim of DEIMS-SDR is to be the globally most comprehensive catalogue of environmental research and monitoring facilities, featuring foremost but not exclusively information about all LTER sites on the globe and providing that information to science, politics and the public in general.
The COVID-19 Data Portal was launched in April 2020 to bring together relevant datasets for sharing and analysis in an effort to accelerate coronavirus research. It enables researchers to upload, access and analyse COVID-19 related reference data and specialist datasets as part of the wider European COVID-19 Data Platform.
The NIDDK Information Network (dkNET) serves the needs of basic and clinical investigators by providing seamless access to large pools of data and research resources relevant to the mission of The National Institute of Diabetes Digestive and Kidney Diseases (NIDDK).
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bio.tools is a software registry for bioinformatics and the life sciences.
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From 2005 to 2008, with the support of the Ministry of Science and Technology (MOST), the construction of parasite germplasm repositories has spread to 20 conservation institutions in 15 provinces (cities) nationwide, with 3 physical exhibition halls; 3 live parasite conservation centers. A total of 1115 species/117814 pieces of parasitic germplasm resources of 23 orders in 11 phyla have been integrated into the physical library and database, including human parasites and vectors, animal parasites, plant nematodes, medical insects, trematodes, and parasitic snails, and the resources are combined with moderate distribution, medium- and long-term support, and off-site duplicates. The number of resources accounts for 39.27% of the national total. Through 10 years of accumulation, we have built the largest and only parasite species resource database in the field of parasites in China, and created a sharing platform of parasite germplasm resource center.
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The Antibody Registry supports the RRID Initiative and exists to give researchers a way to universally identify antibodies used in publications. The registry lists many commercial antibodies from over 200 vendors, which have been assigned a unique identifier and over 2000 individual laboratories. If the antibody that you are using does not appear in the list, an entry can be made by filling in as little as 2 pieces of information: the catalog number and the url of the vendor where our curators can find information and material data sheets.
PSnpBind is a large database of protein–ligand complexes covering a wide range of binding pocket mutations and small molecules’ landscape. This database can be used as a source of data for different types of studies, for example, developing machine learning algorithms to predict protein–ligand affinity or mutation's effect on it which requires an extensive amount of data with a wide coverage of mutation types and small molecules. Also, studies of protein-ligand interactions and conformer orientation changes across different mutated versions of a protein can be established using data from PSnpBind.
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With the KIT Whole-Body Human Motion Database, we aim to provide a simple way of sharing high-quality motion capture recordings of human whole-body motion. In addition, with the Motion Annotation Tool (https://motion-annotation.humanoids.kit.edu/ ), we aim to collect a comprehensive set of whole-body motions along with natural language descriptions of these motions (https://motion-annotation.humanoids.kit.edu/dataset/).
The Antimicrobial Peptide Database (APD) was originally created by a graduate student, Zhe Wang, as his master's thesis in the laboratory of Dr. Guangshun Wang. The project was initiated in 2002 and the first version of the database was open to the public in August 2003. It contained 525 peptide entries, which can be searched in multiple ways, including APD ID, peptide name, amino acid sequence, original location, PDB ID, structure, methods for structural determination, peptide length, charge, hydrophobic content, antibacterial, antifungal, antiviral, anticancer, and hemolytic activity. Some results of this bioinformatics tool were reported in the 2004 database paper. The peptide data stored in the APD were gleaned from the literature (PubMed, PDB, Google, and Swiss-Prot) manually in over a decade.