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Found 395 result(s)
!!! >>> intrepidbio.com expired <<< !!!! Intrepid Bioinformatics serves as a community for genetic researchers and scientific programmers who need to achieve meaningful use of their genetic research data – but can’t spend tremendous amounts of time or money in the process. The Intrepid Bioinformatics system automates time consuming manual processes, shortens workflow, and eliminates the threat of lost data in a faster, cheaper, and better environment than existing solutions. The system also provides the functionality and community features needed to analyze the large volumes of Next Generation Sequencing and Single Nucleotide Polymorphism data, which is generated for a wide range of purposes from disease tracking and animal breeding to medical diagnosis and treatment.
An open digital archive of scholarly, intellectual and research outputs of the University of South Africa. The UnisaIR contains and preserves theses and dissertations, research articles, conference papers, rare and special materials and many other digital assets. With special collections from the Documentation Center for African Studies including manuscripts, photos, political posters and other archival materials about the history of South Africa.
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Silkworm Pathogen Database (SilkPathDB) is a comprehensive resource for studying on pathogens of silkworm, including microsporidia, fungi, bacteria and virus. SilkPathDB provides access to not only genomic data including functional annotation of genes and gene products, but also extensive biological information for gene expression data and corresponding researches. SilkPathDB will be help with researches on pathogens of silkworm as well as other Lepidoptera insects.
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The RAMEDIS system is a platform independent, web-based information system for rare metabolic diseases based on filed case reports. It was developed in close cooperation with clinical partners to allow them to collect information on rare metabolic diseases with extensive details, e.g. about occurring symptoms, laboratory findings, therapy and molecular data.
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data.public.lu is Luxembourg's central and official platform for data from the public sector, from research institutes and the private sector.
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KRISHI Portal is an initiative of Indian Council of Agricultural Research (ICAR) to bring its knowledge resources to all stakeholders at one place. The portal is being developed as a centralized data repository system of ICAR consisting of Technology, Data generated through Experiments/ Surveys/ Observational studies, Geo-spatial data, Publications, Learning Resources etc. For implementation of research data management electronically in ICAR Institutes and digitization of agricultural research, KRISHI (Knowledge based Resources Information Systems Hub for Innovations in Agriculture) Portal has been developed as ICAR Research Data Repository for knowledge management. Data Inventory Repository aims at creating Meta Data Inventory through information related to data availability at Institute level. The portal consists of six repositories viz. technology, publication, experimental data, observational data survey data and geo-portal. The portal can be accessed at http://krishi.icar.gov.in. During the period of 2016-17, input data on latitude and longitude of all KVKs under this Zone was submitted to the concerned authority to put them in geo-portal. One brainstorming session was organized at this institute for all scientists on its use and uploading information in portal. As per guidelines of the council, various kinds of publications pertaining to this institute were also uploaded in this portal.
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The Libraries offer members of the Université de Montréal community the opportunity to publish their research data in a Dataverse repository space
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The Open Archive for Miscellaneous Data (OMIX) database is a data repository developed and maintained by the National Genomics Data Center (NGDC). The database specializes in descriptions of biological studies, including genomic, proteomic, and metabolomic, as well as data that do not fit in the structured archives at other databases in NGDC. It can accept various types of studies described via a simple format and enables researchers to upload supplementary information and link to it from the publication.
Brain Image Library (BIL) is an NIH-funded public resource serving the neuroscience community by providing a persistent centralized repository for brain microscopy data. Data scope of the BIL archive includes whole brain microscopy image datasets and their accompanying secondary data such as neuron morphologies, targeted microscope-enabled experiments including connectivity between cells and spatial transcriptomics, and other historical collections of value to the community. The BIL Analysis Ecosystem provides an integrated computational and visualization system to explore, visualize, and access BIL data without having to download it.
Museum explorers travel to ocean depths, the peaks of the Andes, Africa's Rift Valley, the rainforests of South America, and the deserts of Central Asia. Perhaps even to a field site or research institution in your own state, territory or country. In each area, researchers collect specimens: fossils, minerals, and rocks, plants and animals, tools and artworks. Collections care professionals have meticulously preserved, labeled, cataloged, and organized items of this kind for more than 150 years. Taken together, the NMNH collections form the largest, most comprehensive natural history collection in the world. By comparing items gathered in different eras and regions, scientists learn how our world has varied across time and space.
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On this server you'll find 127 items of primary data of the University of Munich. Scientists / students of all faculties of LMU and of institutions that cooperate with the LMU are invited to deposit their research data on this platform.
OMIM is a comprehensive, authoritative compendium of human genes and genetic phenotypes that is freely available and updated daily. OMIM is authored and edited at the McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, under the direction of Dr. Ada Hamosh. Its official home is omim.org.
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The National Microbial Data Center (NMDC) is jointly constructed by the Institute of Microbiology of the Chinese Academy of Sciences (IMS), the Institute of Oceanography of the Chinese Academy of Sciences, the Institute of Infectious Diseases of the Chinese Center for Disease Control and Prevention, the Institute of Plant Physiology and Ecology of the Chinese Academy of Sciences, and the Computer Network Information Centre of the Chinese Academy of Sciences. The General Office of the Chinese Academy of Sciences is the parent department. The data resources covering the whole life cycle of microbiological research, including microbiological resources, microbiological and cross-technological methods, research processes and engineering, microbiomics, microbiological technologies, as well as microbiological literature, patents, experts and results. The Centre focuses on promoting the convergence and integration of scientific and technological resources in the field of microbiology to the national platform, strengthening the development, application and analysis of microbiological resources, enhancing the effective use of microbiological resources and the ability to support scientific and technological innovation, and providing high-quality scientific and technological resource sharing services for scientific research, technological progress and social development.
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GRO.data is a research data repository for the Göttingen Campus. Belonging researchers can use it for free. It serves different purposes such as: to simply preserve datasets, to keep track of changes across several versions, to share data with colleagues, to make data itself publicly available, to receive a persistent identifier upon publications.
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The Atlantic Canada Conservation Data Centre (ACCDC) maintains comprehensive lists of plant and animal species. The Atlantic CDC has geo-located records of species occurrences and records of extremely rare to uncommon species in the Atlantic region, including New Brunswick, Nova Scotia, Prince Edward Island, Newfoundland, and Labrador. The Atlantic CDC also maintains biological and other types of data in a variety of linked databases.
The USDA Economics, Statistics and Market Information System contains reports and datasets of multiple agencies within the United States Department of Agriculture, including the Agricultural Marketing Service, the Economic Research Service, the Foreign Agricultural Service, the National Agricultural Statistics Service, and the World Agricultural Outlook Board. Historical and current reports and datasets are included.
The Comprehensive Epidemiologic Data Resource (CEDR) is the U.S. Department of Energy (DOE) electronic database comprised of health studies of DOE contract workers and environmental studies of areas surrounding DOE facilities. DOE recognizes the benefits of data sharing and supports the public's right to know about worker and community health risks. CEDR provides independent researchers and educators with access to de-identified data collected since the Department's early production years. Current CEDR holdings include more than 76 studies of over 1 million workers at 31 DOE sites. Access to these data is at no cost to the user.
OrthoMCL is a genome-scale algorithm for grouping orthologous protein sequences. It provides not only groups shared by two or more species/genomes, but also groups representing species-specific gene expansion families. So it serves as an important utility for automated eukaryotic genome annotation. OrthoMCL starts with reciprocal best hits within each genome as potential in-paralog/recent paralog pairs and reciprocal best hits across any two genomes as potential ortholog pairs. Related proteins are interlinked in a similarity graph. Then MCL (Markov Clustering algorithm,Van Dongen 2000; www.micans.org/mcl) is invoked to split mega-clusters. This process is analogous to the manual review in COG construction. MCL clustering is based on weights between each pair of proteins, so to correct for differences in evolutionary distance the weights are normalized before running MCL.
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.
The Plant Metabolic Network (PMN) provides a broad network of plant metabolic pathway databases that contain curated information from the literature and computational analyses about the genes, enzymes, compounds, reactions, and pathways involved in primary and secondary metabolism in plants. The PMN currently houses one multi-species reference database called PlantCyc and 22 species/taxon-specific databases.
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The Organelle Genome Megasequencing Program (OGMP) provides mitochondrial, chloroplast, and mitochondrial plasmid genome data. OGMP tools allow direct comparison of OGMP and NCBI validated records. Includes GOBASE, a taxonomically broad organelle genome database that organizes and integrates diverse data related to mitochondria and chloroplasts.
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The FDZ-DZA (Forschungsdatenzentrum DZA) is a facility of the German Centre of Gerontology (Deutsches Zentrum für Altersfragen, DZA) and has received accreditation as research data center DZA by the German Data Forum (RatSWD). Its main task is to make data of the German Ageing Survey DEAS and the German Survey on Volunteering (FWS) accessible to researchers by providing user-friendly Scientific Use Files (SUF), documentation of the contents and instruments as well support for scholars using the data.
STRING is a database of known and predicted protein interactions. The interactions include direct (physical) and indirect (functional) associations; they are derived from four sources: - Genomic Context - High-throughput Experiments - (Conserved) Coexpression - Previous Knowledge STRING quantitatively integrates interaction data from these sources for a large number of organisms, and transfers information between these organisms where applicable.