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Found 56 result(s)
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.
>>>!!!<<< caArray Retirement Announcement >>>!!!<<< The National Cancer Institute (NCI) Center for Biomedical Informatics and Information Technology (CBIIT) instance of the caArray database was retired on March 31st, 2015. All publicly-accessible caArray data and annotations will be archived and will remain available via FTP download https://wiki.nci.nih.gov/x/UYHeDQ and is also available at GEO http://www.ncbi.nlm.nih.gov/geo/ . >>>!!!<<< While NCI will not be able to provide technical support for the caArray software after the retirement, the source code is available on GitHub https://github.com/NCIP/caarray , and we encourage continued community development. Molecular Analysis of Brain Neoplasia (Rembrandt fine-00037) gene expression data has been loaded into ArrayExpress: http://www.ebi.ac.uk/arrayexpress/experiments/E-MTAB-3073 >>>!!!<<< caArray is an open-source, web and programmatically accessible microarray data management system that supports the annotation of microarray data using MAGE-TAB and web-based forms. Data and annotations may be kept private to the owner, shared with user-defined collaboration groups, or made public. The NCI instance of caArray hosts many cancer-related public datasets available for download.
The NCBI Short Genetic Variations database, commonly known as dbSNP, catalogs short variations in nucleotide sequences from a wide range of organisms. These variations include single nucleotide variations, short nucleotide insertions and deletions, short tandem repeats and microsatellites. Short Genetic Variations may be common, thus representing true polymorphisms, or they may be rare. Some rare human entries have additional information associated withthem, including disease associations, genotype information and allele origin, as some variations are somatic rather than germline events. ***NCBI will phase out support for non-human organism data in dbSNP and dbVar beginning on September 1, 2017***
The dbVar is a database of genomic structural variation containing data from multiple gene studies. Users can browse data containing the number of variant cells from each study, and filter studies by organism, study type, method and genomic variant. Organisms include human, mouse, cattle and several additional animals. ***NCBI will phase out support for non-human organism data in dbSNP and dbVar beginning on September 1, 2017 ***
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CORUM is a manually curated dataset of mammalian protein complexes. Annotation of protein complexes includes protein complex composition and other valuable information such as method of purification, cellular function of complexes or involvement in diseases.
This resource allows users to search for and compare influenza virus genomes and gene sequences taken from GenBank. It also provides a virus sequence annotation tool and links to other influenza resources: NIAID project, JCVI Flu, Influenza research database, CDC Flu, Vaccine Selection and WHO Flu. NOTE: The redirects that are planned for completion by May 2024 will NOT impact the Influenza Virus Resource in any way. The Influenza Virus Resource will continue to be available, serving up data to support our Flu-research community.
<<<!!!<<< 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. >>>!!!>>>
<<<!!!<<< 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 NCBI BioSystems Database will be retired in March 2022. >>>!!!>>> This retirement includes the representation of BioSystems records in the NCBI Entrez system and viewers of BioSystems content. NCBI now provides metabolic pathway and other biosystems data through the regularly updated PubChem Pathways resource (https://pubchemdocs.ncbi.nlm.nih.gov/pathways) that offers a fresh, extended, and more modern interface.
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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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.
The Gene database provides detailed information for known and predicted genes defined by nucleotide sequence or map position. Gene supplies gene-specific connections in the nexus of map, sequence, expression, structure, function, citation, and homology data. Unique identifiers are assigned to genes with defining sequences, genes with known map positions, and genes inferred from phenotypic information. These gene identifiers are used throughout NCBI's databases and tracked through updates of annotation. Gene includes genomes represented by NCBI Reference Sequences (or RefSeqs) and is integrated for indexing and query and retrieval from NCBI's Entrez and E-Utilities systems.
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.
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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.
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 NCBI database of Genotypes and Phenotypes archives and distributes the results of studies that have investigated the interaction of genotype and phenotype, including genome-wide association studies, medical sequencing, molecular diagnostic assays, and association between genotype and non-clinical traits. The database provides summaries of studies, the contents of measured variables, and original study document text. dbGaP provides two types of access for users, open and controlled. Through the controlled access, users may access individual-level data such as phenotypic data tables and genotypes.
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 HomoloGene database provides a system for the automated detection of homologs among annotated genes of genomes across multiple species. These homologs are fully documented and organized by homology group. HomoloGene processing uses proteins from input organisms to compare and sequence homologs, mapping back to corresponding DNA sequences.