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Found 26 result(s)
The GWAS Catalog is an open access repository of all human genome wide association studies. It is considered the “go-to” resource for genetic evidence of associations between common genetic variation and diseases or phenotypes, is accessed by scientists, clinicians and other users worldwide, and is integrated with numerous other resources. Association data and metadata are identified and extracted from the scientific literature by expert data curators. Submissions of full genome wide summary data can be made directly by authors, either before or after journal publication.
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.
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NODE (The National Omics Data Encyclopedia) provides an integrated, compatible, comparable, and scalable multi-omics resource platform that supports flexible data management and effective data release. NODE uses a hierarchical data architecture to support storage of muti-omics data including sequencing data, MS based proteomics data, MS or NMR based metabolomics data, and fluorescence imaging data. Launched in early 2017, NODE has collected and published over 900 terabytes of omics data for researchers from China and all over the world in last three years, 22% of which contains multiple omics data. NODE provides functions around the whole life cycle of omics data, from data archive, data requests/responses to data sharing, data analysis, data review and publish.
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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.
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KEGG is a database resource for understanding high-level functions and utilities of the biological system, such as the cell, the organism and the ecosystem, from molecular-level information, especially large-scale molecular datasets generated by genome sequencing and other high-throughput experimental technologies
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.
<<<!!!<<< Effective May 2024, NCBI's Genome resource will no longer be available. NCBI Genome data can now be found on the NCBI Datasets taxonomy pages. https://www.re3data.org/repository/r3d100014298 >>>!!!>>> The Genome database contains annotations and analysis of eukaryotic and prokaryotic genomes, as well as tools that allow users to compare genomes and gene sequences from humans, microbes, plants, viruses and organelles. Users can browse by organism, and view genome maps and protein clusters.
<<<!!!<<< The repository is no longer available - Data previously on the site are now available at ftp://ftp.ncbi.nlm.nih.gov/pub/mhc/mhc/Final Archive. >>>!!!>>> The dbMHC database provides an open, publicly accessible platform for DNA and clinical data related to the human Major Histocompatibility Complex (MHC). The dbMHC provides access to human leukocyte antigen (HLA) sequences, HLA allele and haplotype frequencies, and clinical datasets.
<<<!!!<<< 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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The Global Proteome Machine (GPM) is a protein identification database. This data repository allows users to post and compare results. GPM's data is provided by contributors like The Informatics Factory, University of Michigan, and Pacific Northwestern National Laboratories. The GPM searchable databases are: GPMDB, pSYT, SNAP, MRM, PEPTIDE and HOT.
<<<!!!<<< NCBI announced plans to retire the Clone DB web interface. Pursuant to this retirement, starting on May 27, 2019, all web pages associated with Clone DB and CloneFinder will redirect to this blog post https://ncbiinsights.ncbi.nlm.nih.gov/?s=clone+db. Links to Clone DB from the NCBI home page will also be going away. >>>!!!>>>
GigaDB primarily serves as a repository to host data and tools associated with articles published by GigaScience Press; GigaScience and GigaByte (both are online, open-access journals). GigaDB defines a dataset as a group of files (e.g., sequencing data, analyses, imaging files, software programs) that are related to and support a unit-of-work (article or study). GigaDB allows the integration of manuscript publication with supporting data and tools.
AceView provides a curated, comprehensive and non-redundant sequence representation of all public mRNA sequences (mRNAs from GenBank or RefSeq, and single pass cDNA sequences from dbEST and Trace). These experimental cDNA sequences are first co-aligned on the genome then clustered into a minimal number of alternative transcript variants and grouped into genes. Using exhaustively and with high quality standards the available cDNA sequences evidences the beauty and complexity of mammals’ transcriptome, and the relative simplicity of the nematode and plant transcriptomes. Genes are classified according to their inferred coding potential; many presumably non-coding genes are discovered. Genes are named by Entrez Gene names when available, else by AceView gene names, stable from release to release. Alternative features (promoters, introns and exons, polyadenylation signals) and coding potential, including motifs, domains, and homologies are annotated in depth; tissues where expression has been observed are listed in order of representation; diseases, phenotypes, pathways, functions, localization or interactions are annotated by mining selected sources, in particular PubMed, GAD and Entrez Gene, and also by performing manual annotation, especially in the worm. In this way, both the anatomy and physiology of the experimentally cDNA supported human, mouse and nematode genes are thoroughly annotated.
>>> !!!!! The Cell Centered Database is no longer on serice. It has been merged with "Cell image library": https://www.re3data.org/repository/r3d100000023 !!!!! <<<<
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.
<<<!!!<<< This repository is no longer available. >>>!!!>>> PATRIC will go offline by mid-December2022. Here is what you need to know. As announced previously, PATRIC, the bacterial BRC, and IRD / ViPR, the viral BRCs, are being merged into the new Bacterial and Viral Bioinformatics Resource Center (BV-BRC). BV-BRC combines the data, tools, and technologies from these BRCs to provide an integrated resource for bacterial and viral genomics-based infectious disease research.
GeneLab is an interactive, open-access resource where scientists can upload, download, store, search, share, transfer, and analyze omics data from spaceflight and corresponding analogue experiments. Users can explore GeneLab datasets in the Data Repository, analyze data using the Analysis Platform, and create collaborative projects using the Collaborative Workspace. GeneLab promises to facilitate and improve information sharing, foster innovation, and increase the pace of scientific discovery from extremely rare and valuable space biology experiments. Discoveries made using GeneLab have begun and will continue to deepen our understanding of biology, advance the field of genomics, and help to discover cures for diseases, create better diagnostic tools, and ultimately allow astronauts to better withstand the rigors of long-duration spaceflight. GeneLab helps scientists understand how the fundamental building blocks of life itself – DNA, RNA, proteins, and metabolites – change from exposure to microgravity, radiation, and other aspects of the space environment. GeneLab does so by providing fully coordinated epigenomics, genomics, transcriptomics, proteomics, and metabolomics data alongside essential metadata describing each spaceflight and space-relevant experiment. By carefully curating and implementing best practices for data standards, users can combine individual GeneLab datasets to gain new, comprehensive insights about the effects of spaceflight on biology. In this way, GeneLab extends the scientific knowledge gained from each biological experiment conducted in space, allowing scientists from around the world to make novel discoveries and develop new hypotheses from these priceless data.
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>>>!!!<<< The repository is no longer available. >>>!!!<<< Indian Genetic Disease Database (IGDD) is an initiative of CSIR Indian Institute of Chemical Biology. It is supported by Council of Scientific and Industrial Research (CSIR) and Department of Biotechnology (DBT) of India. The Indian people represent one-sixth of the world population and consists of a ethnically, geographically, and genetically diverse population. In some communities the ratio of genetic disorder is relatively high due to consanguineous marriage practiced in the community. This database has been created to keep track of mutations in the causal genes for genetic diseases common in India and help the physicians, geneticists, and other professionals retrieve and use the information for the benefit of the public. The database includes scientific information about these genetic diseases and disabilities, but also statistical information about these diseases in today's society. Data is categorized by body part affected and then by title of the disease.
The ENCODE Encyclopedia organizes the most salient analysis products into annotations, and provides tools to search and visualize them. The Encyclopedia has two levels of annotations: Integrative-level annotations integrate multiple types of experimental data and ground level annotations. Ground-level annotations are derived directly from the experimental data, typically produced by uniform processing pipelines.
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The Human Genetic Variation Database (HGVD) aims to provide a central resource to archive and display Japanese genetic variation and association between the variation and transcription level of genes. The database currently contains genetic variations determined by exome sequencing of 1,208 individuals and genotyping data of common variations obtained from a cohort of 3,248 individuals.
The European Genome-phenome Archive (EGA) is designed to be a repository for all types of sequence and genotype experiments, including case-control, population, and family studies. We will include SNP and CNV genotypes from array based methods and genotyping done with re-sequencing methods. The EGA will serve as a permanent archive that will archive several levels of data including the raw data (which could, for example, be re-analysed in the future by other algorithms) as well as the genotype calls provided by the submitters. We are developing data mining and access tools for the database. For controlled access data, the EGA will provide the necessary security required to control access, and maintain patient confidentiality, while providing access to those researchers and clinicians authorised to view the data. In all cases, data access decisions will be made by the appropriate data access-granting organisation (DAO) and not by the EGA. The DAO will normally be the same organisation that approved and monitored the initial study protocol or a designate of this approving organisation. The European Genome-phenome Archive (EGA) allows you to explore datasets from genomic studies, provided by a range of data providers. Access to datasets must be approved by the specified Data Access Committee (DAC).