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Found 221 result(s)
TPA is a database that contains sequences built from the existing primary sequence data in GenBank. TPA records are retrieved through the Nucleotide Database and feature information on the sequence, how it was cataloged, and proper way to cite the sequence information.
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Repository "Open Science Resource Atlas 2.0" aims to increase the accessibility, improve the quality and extend the reusability of science resources. Repository focuses on the digital sharing of resources of great importance to the field of science and economy. These include publications, scripts, lectures, 3D models, audio and video recordings, photos, input and output files of various computer programs, databases collecting data from various fields, machines, systems, language corpora and many others. The target group, apart from academics, students and doctoral students, is everyone interested, including entrepreneurs and, what is important and unique - disabled, blind, visually impaired and deaf people.
<<<!!!<<< USHIK was archived because some of the metadata are maintained by other sites and there is no need for duplication. The USHIK metadata registry was a neutral repository of metadata from an authoritative source used to promote interoperability and reuse of data. The registry did not attempt to change the metadata content but rather provided a structured way to view data for the technical or casual user. Complete information see: https://www.ahrq.gov/data/ushik.html >>>!!!>>>
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The Chickpea Transcriptome Database (CTDB) has been developed with the view to provide most comprehensive information about the chickpea transcriptome, the most relevant part of the genome. The database contains various information and tools for transcriptome sequence, functional annotation, conserved domain(s), transcription factor families, molecular markers (microsatellites and single nucleotide polymorphisms), Comprehensive gene expression and comparative genomics with other legumes. The database is a freely available resource, which provides user scientists/breeders a portal to search, browse and query the data to facilitate functional and applied genomics research in chickpea and other legumes. The current release of database provides transcriptome sequence from cultivated (Cicer arietinum desi (ICC4958) and kabuli (ICCV2)) and wild (Cicer reticulatum, PI489777) chickpea genotypes.
The Allele Frequency Net Database (AFND) is a public database which contains frequency information of several immune genes such as Human Leukocyte Antigens (HLA), Killer-cell Immunoglobulin-like Receptors (KIR), Major histocompatibility complex class I chain-related (MIC) genes, and a number of cytokine gene polymorphisms. The Allele Frequency Net Database (AFND) provides a central source, freely available to all, for the storage of allele frequencies from different polymorphic areas in the Human Genome. Users can contribute the results of their work into one common database and can perform database searches on information already available. We have currently collected data in allele, haplotype and genotype format. However, the success of this website will depend on you to contribute your data.
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The CEBS database houses data of interest to environmental health scientists. CEBS is a public resource, and has received depositions of data from academic, industrial and governmental laboratories. CEBS is designed to display data in the context of biology and study design, and to permit data integration across studies for novel meta analysis.
With the creation of the Metabolomics Data Repository managed by Data Repository and Coordination Center (DRCC), the NIH acknowledges the importance of data sharing for metabolomics. Metabolomics represents the systematic study of low molecular weight molecules found in a biological sample, providing a "snapshot" of the current and actual state of the cell or organism at a specific point in time. Thus, the metabolome represents the functional activity of biological systems. As with other ‘omics’, metabolites are conserved across animals, plants and microbial species, facilitating the extrapolation of research findings in laboratory animals to humans. Common technologies for measuring the metabolome include mass spectrometry (MS) and nuclear magnetic resonance spectroscopy (NMR), which can measure hundreds to thousands of unique chemical entities. Data sharing in metabolomics will include primary raw data and the biological and analytical meta-data necessary to interpret these data. Through cooperation between investigators, metabolomics laboratories and data coordinating centers, these data sets should provide a rich resource for the research community to enhance preclinical, clinical and translational research.
The OFA databases are core to the organization’s objective of establishing control programs to lower the incidence of inherited disease. Responsible breeders have an inherent responsibility to breed healthy dogs. The OFA databases serve all breeds of dogs and cats, and provide breeders a means to respond to the challenge of improving the genetic health of their breed through better breeding practices. The testing methodology and the criteria for evaluating the test results for each database were independently established by veterinary scientists from their respective specialty areas, and the standards used are generally accepted throughout the world.
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TUdatalib is the institutional repository of the TU Darmstadt for research data. It enables the structured storage of research data and descriptive metadata, long-term archiving (at least 10 years) and, if desired, the publication of data including DOI assignment. In addition there is a fine granular rights and role management.
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FinBIF is an integral part of the global biodiversity informatics framework, dedicated to managing species information. Its mission encompasses a wide array of services, including the generation of digital data through various processes, as well as the sourcing, collation, integration, and distribution of existing digital data. Key initiatives under FinBIF include the digitization of collections, the development of data systems for collections Kotka (https://biss.pensoft.net/article/37179/) and observations (https://biss.pensoft.net/article/39150/), and the establishment of a national DNA barcode reference library. FinBIF manages data types such as verbal species descriptions (which include drawings, pictures, and other media types), biological taxonomy, scientific collection specimens, opportunistic systematic and event-based observations, and DNA barcodes. It employs a unified IT architecture to manage data flows, delivers services through a single online portal, fosters collaboration under a cohesive umbrella concept, and articulates development visions under a unified brand. The portal Laji.fi serves as the entry point to this harmonized open data ecosystem. FinBIF's portal is accessible in Finnish, Swedish, and English. Data intended for restricted use are made available to authorities through a separate portal, while open data are also shared with international systems, such as GBIF.
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Stemformatics is a collaboration between the stem cell and bioinformatics community. We were motivated by the plethora of exciting cell models in the public and private domains, and the realisation that for many biologists these were mostly inaccessible. We wanted a fast way to find and visualise interesting genes in these exemplar stem cell datasets. We'd like you to explore. You'll find data from leading stem cell laboratories in a format that is easy to search, easy to visualise and easy to export.
The Behavioral Risk Factor Surveillance System (BRFSS) is the world's largest, on-going telephone health survey system. As a result, surveys were developed and conducted to monitor state-level prevalence of the major behavioral risks among adults associated with premature morbidity and mortality. The basic philosophy was to collect data on actual behaviors, rather than on attitudes or knowledge, that would be especially useful for planning, initiating, supporting, and evaluating health promotion and disease prevention programs. Currently data are collected monthly in all 50 states.
The BBS is a cooperative effort between the U.S. Geological Survey's Patuxent Wildlife Research Center and Environment Canada's Canadian Wildlife Service to monitor the status and trends of North American bird populations. Following a rigorous protocol, BBS data are collected by thousands of dedicated participants along thousands of randomly established roadside routes throughout the continent. Professional BBS coordinators and data managers work closely with researchers and statisticians to compile and deliver these population data and population trend analyses on more than 400 bird species, for use by conservation managers, scientists, and the general public.
<<<!!!<<< The page is no longer available. This database was already retired, and on this page users could find information on how to search and use these sequences. dbSTS was an NCBI resource that contained sequence data for short genomic landmark sequences or Sequence Tagged Sites. STS sequences are incorporated into the STS Division of GenBank. >>>!!!>>>
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>>>!!!<<<As stated 2017-05-23 Cancer GEnome Mine is no longer available >>>!!!<<< Cancer GEnome Mine is a public database for storing clinical information about tumor samples and microarray data, with emphasis on array comparative genomic hybridization (aCGH) and data mining of gene copy number changes.
The miRBase database is a searchable database of published miRNA sequences and annotation. Each entry in the miRBase Sequence database represents a predicted hairpin portion of a miRNA transcript (termed mir in the database), with information on the location and sequence of the mature miRNA sequence (termed miR). Both hairpin and mature sequences are available for searching and browsing, and entries can also be retrieved by name, keyword, references and annotation. All sequence and annotation data are also available for download. The miRBase Registry provides miRNA gene hunters with unique names for novel miRNA genes prior to publication of results.
Weed Images is a project of the University of Georgia’s Center for Invasive Species and Ecosystem Health and one of the four major parts of BugwoodImages. The Focus is on damages of weed. It provides an easily accessible archive of high quality images for use in educational applications. In most cases, the images found in this system were taken by and loaned to us by photographers other than ourselves. Most are in the realm of public sector images. The photographs are in this system to be used.