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Found 120 result(s)
The NCI's Genomic Data Commons (GDC) provides the cancer research community with a unified data repository that enables data sharing across cancer genomic studies in support of precision medicine. The GDC obtains validated datasets from NCI programs in which the strategies for tissue collection couples quantity with high quality. Tools are provided to guide data submissions by researchers and institutions.
!!! >>> the repository is offline >>> !!! GOBASE is a taxonomically broad organelle genome database that organizes and integrates diverse data related to mitochondria and chloroplasts. GOBASE is currently expanding to include information on representative bacteria that are thought to be specifically related to the bacterial ancestors of mitochondria and chloroplasts
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Morph·D·Base has been developed to serve scientific research and education. It provides a platform for storing the detailed documentation of all material, methods, procedures, and concepts applied, together with the specific parameters, values, techniques, and instruments used during morphological data production. In other words, it's purpose is to provide a publicly available resource for recording and documenting morphological metadata. Moreover, it is also a repository for different types of media files that can be uploaded in order to serve as support and empirical substantiation of the results of morphological investigations. Our long-term perspective with Morph·D·Base is to provide an instrument that will enable a highly formalized and standardized way of generating morphological descriptions using a morphological ontology that will be based on the web ontology language (OWL - http://www.w3.org/TR/owl-features/). This, however, represents a project that is still in development.
The National Sleep Research Resource (NSRR) is an NHLBI-supported repository for sharing large amounts of sleep data (polysomnography, actigraphy and questionnaire-based) from multiple cohorts, clinical trials, and other data sources. Launched in April 2014, the mission of the NSRR is to advance sleep and circadian science by supporting secondary data analysis, algorithmic development, and signal processing through the sharing of high-quality data sets.
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DataverseNO (https://dataverse.no) is a curated, FAIR-aligned national generic repository for open research data from all academic disciplines. DataverseNO commits to facilitate that published data remain accessible and (re)usable in a long-term perspective. The repository is owned and operated by UiT The Arctic University of Norway. DataverseNO accepts submissions from researchers primarily from Norwegian research institutions. Datasets in DataverseNO are grouped into institutional collections as well as special collections. The technical infrastructure of the repository is based on the open source application Dataverse (https://dataverse.org), which is developed by an international developer and user community led by Harvard University.
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The DrugBank database is a unique bioinformatics and cheminformatics resource that combines detailed drug (i.e. chemical, pharmacological and pharmaceutical) data with comprehensive drug target (i.e. sequence, structure, and pathway) information. The latest release of DrugBank (version 5.1.1, released 2018-07-03) contains 11,881 drug entries including 2,526 approved small molecule drugs, 1,184 approved biotech (protein/peptide) drugs, 129 nutraceuticals and over 5,751 experimental drugs. Additionally, 5,132 non-redundant protein (i.e. drug target/enzyme/transporter/carrier) sequences are linked to these drug entries. Each DrugCard entry contains more than 200 data fields with half of the information being devoted to drug/chemical data and the other half devoted to drug target or protein 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.
We are working on a new version of ALFRED web interface. The current web interface will not be available from December 15th, 2023. There will be a period where a public web interface is not available for viewing ALFRED data. Expected date for the deployment of the new ALFRED web interface with minimum functions is March 1st, 2024 --------------------------------------------- ALFRED is a free, web-accessible, curated compilation of allele frequency data on DNA sequence polymorphisms in anthropologically defined human populations. ALFRED is distinct from such databases as dbSNP, which catalogs sequence variation.
Gemma is a database for the meta-analysis, re-use and sharing of genomics data, currently primarily targeted at the analysis of gene expression profiles. Gemma contains data from thousands of public studies, referencing thousands of published papers. Users can search, access and visualize co-expression and differential expression results.
The Humanitarian Data Exchange (HDX) is an open platform for sharing data across crises and organisations. Launched in July 2014, the goal of HDX is to make humanitarian data easy to find and use for analysis. HDX is managed by OCHA's Centre for Humanitarian Data, which is located in The Hague. OCHA is part of the United Nations Secretariat and is responsible for bringing together humanitarian actors to ensure a coherent response to emergencies. The HDX team includes OCHA staff and a number of consultants who are based in North America, Europe and Africa.
OrtholugeDB contains Ortholuge-based orthology predictions for completely sequenced bacterial and archaeal genomes. It is also a resource for reciprocal best BLAST-based ortholog predictions, in-paralog predictions (recently duplicated genes) and ortholog groups in Bacteria and Archaea. The Ortholuge method improves the specificity of high-throughput orthology prediction.
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During cell cycle, numerous proteins temporally and spatially localized in distinct sub-cellular regions including centrosome (spindle pole in budding yeast), kinetochore/centromere, cleavage furrow/midbody (related or homolog structures in plants and budding yeast called as phragmoplast and bud neck, respectively), telomere and spindle spatially and temporally. These sub-cellular regions play important roles in various biological processes. In this work, we have collected all proteins identified to be localized on kinetochore, centrosome, midbody, telomere and spindle from two fungi (S. cerevisiae and S. pombe) and five animals, including C. elegans, D. melanogaster, X. laevis, M. musculus and H. sapiens based on the rationale of "Seeing is believing" (Bloom K et al., 2005). Through ortholog searches, the proteins potentially localized at these sub-cellular regions were detected in 144 eukaryotes. Then the integrated and searchable database MiCroKiTS - Midbody, Centrosome, Kinetochore, Telomere and Spindle has been established.
Human Protein Reference Database (HPRD) has been established by a team of biologists, bioinformaticists and software engineers. This is a joint project between the PandeyLab at Johns Hopkins University, and Institute of Bioinformatics, Bangalore. HPRD is a definitive repository of human proteins. This database should serve as a ready reckoner for researchers in their quest for drug discovery, identification of disease markers and promote biomedical research in general. Human Proteinpedia (www.humanproteinpedia.org) is its associated data portal.
<<<!!!<<< OFFLINE >>>!!!>>> A recent computer security audit has revealed security flaws in the legacy HapMap site that require NCBI to take it down immediately. We regret the inconvenience, but we are required to do this. That said, NCBI was planning to decommission this site in the near future anyway (although not quite so suddenly), as the 1,000 genomes (1KG) project has established itself as a research standard for population genetics and genomics. NCBI has observed a decline in usage of the HapMap dataset and website with its available resources over the past five years and it has come to the end of its useful life. The International HapMap Project is a multi-country effort to identify and catalog genetic similarities and differences in human beings. Using the information in the HapMap, researchers will be able to find genes that affect health, disease, and individual responses to medications and environmental factors. The Project is a collaboration among scientists and funding agencies from Japan, the United Kingdom, Canada, China, Nigeria, and the United States. All of the information generated by the Project will be released into the public domain. The goal of the International HapMap Project is to compare the genetic sequences of different individuals to identify chromosomal regions where genetic variants are shared. By making this information freely available, the Project will help biomedical researchers find genes involved in disease and responses to therapeutic drugs. In the initial phase of the Project, genetic data are being gathered from four populations with African, Asian, and European ancestry. Ongoing interactions with members of these populations are addressing potential ethical issues and providing valuable experience in conducting research with identified populations. Public and private organizations in six countries are participating in the International HapMap Project. Data generated by the Project can be downloaded with minimal constraints. The Project officially started with a meeting in October 2002 (https://www.genome.gov/10005336/) and is expected to take about three years.
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The Small Molecule Pathway Database (SMPDB) contains small molecule pathways found in humans, which are presented visually. All SMPDB pathways include information on the relevant organs, subcellular compartments, protein cofactors, protein locations, metabolite locations, chemical structures and protein quaternary structures. Accompanying data includes detailed descriptions and references, providing an overview of the pathway, condition or processes depicted in each diagram.
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Addis Ababa University Research Data Repository holds multi disciplinary datasets produced by members of the university.
Reference anatomies of the brain and corresponding atlases play a central role in experimental neuroimaging workflows and are the foundation for reporting standardized results. The choice of such references —i.e., templates— and atlases is one relevant source of methodological variability across studies, which has recently been brought to attention as an important challenge to reproducibility in neuroscience. TemplateFlow is a publicly available framework for human and nonhuman brain models. The framework combines an open database with software for access, management, and vetting, allowing scientists to distribute their resources under FAIR —findable, accessible, interoperable, reusable— principles. TemplateFlow supports a multifaceted insight into brains across species, and enables multiverse analyses testing whether results generalize across standard references, scales, and in the long term, species, thereby contributing to increasing the reliability of neuroimaging results.