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Found 26 result(s)
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.
<<<!!!<<< Phasing out support for the Database of Genomic Variants archive (DGVa). The submission, archiving, and presentation of structural variation services offered by the DGVa is transitioning to the European Variation Archive (EVA) https://www.re3data.org/repository/r3d100011553. All of the data shown in the DGVa website is already searchable and browsable from the EVA Study Browser. Submission of structural variation data to EVA is done using the VCF format. The VCF specification allows representing multiple types of structural variants such as insertions, deletions, duplications and copy-number variants. Other features such as symbolic alleles, breakends, confidence intervals etc., support more complex events, such as translocations at an imprecise position. >>>!!!>>>
The Expression Atlas provides information on gene expression patterns under different biological conditions such as a gene knock out, a plant treated with a compound, or in a particular organism part or cell. It includes both microarray and RNA-seq data. The data is re-analysed in-house to detect interesting expression patterns under the conditions of the original experiment. There are two components to the Expression Atlas, the Baseline Atlas and the Differential Atlas. The Baseline Atlas displays information about which gene products are present (and at what abundance) in "normal" conditions (e.g. tissue, cell type). It aims to answer questions such as "which genes are specifically expressed in human kidney?". This component of the Expression Atlas consists of highly-curated and quality-checked RNA-seq experiments from ArrayExpress. It has data for many different animal and plant species. New experiments are added as they become available. The Differential Atlas allows users to identify genes that are up- or down-regulated in a wide variety of different experimental conditions such as yeast mutants, cadmium treated plants, cystic fibrosis or the effect on gene expression of mind-body practice. Both microarray and RNA-seq experiments are included in the Differential Atlas. Experiments are selected from ArrayExpress and groups of samples are manually identified for comparison e.g. those with wild type genotype compared to those with a gene knock out. Each experiment is processed through our in-house differential expression statistical analysis pipeline to identify genes with a high probability of differential expression.
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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.
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MTD is focused on mammalian transcriptomes with a current version that contains data from humans, mice, rats and pigs. Regarding the core features, the MTD browses genes based on their neighboring genomic coordinates or joint KEGG pathway and provides expression information on exons, transcripts, and genes by integrating them into a genome browser. We developed a novel nomenclature for each transcript that considers its genomic position and transcriptional features.
The MG-RAST server is an open source system for annotation and comparative analysis of metagenomes. Users can upload raw sequence data in fasta format; the sequences will be normalized and processed and summaries automatically generated. The server provides several methods to access the different data types, including phylogenetic and metabolic reconstructions, and the ability to compare the metabolism and annotations of one or more metagenomes and genomes. In addition, the server offers a comprehensive search capability. Access to the data is password protected, and all data generated by the automated pipeline is available for download in a variety of common formats. MG-RAST has become an unofficial repository for metagenomic data, providing a means to make your data public so that it is available for download and viewing of the analysis without registration, as well as a static link that you can use in publications. It also requires that you include experimental metadata about your sample when it is made public to increase the usefulness to the community.
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SILVA is a comprehensive, quality-controlled web resource for up-to-date aligned ribosomal RNA (rRNA) gene sequences from the Bacteria, Archaea and Eukaryota domains alongside supplementary online services. In addition to data products, SILVA provides various online tools such as alignment and classification, phylogenetic tree calculation and viewer, probe/primer matching, and an amplicon analysis pipeline. With every full release a curated guide tree is provided that contains the latest taxonomy and nomenclature based on multiple references. SILVA is an ELIXIR Core Data Resource.
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.
<<<!!!<<< 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.
The IPD-IMGT/HLA Database provides a specialist database for sequences of the human major histocompatibility complex (MHC) and includes the official sequences named by the WHO Nomenclature Committee For Factors of the HLA System. The IPD-IMGT/HLA Database is part of the international ImMunoGeneTics project (IMGT). The database uses the 2010 naming convention for HLA alleles in all tools herein. To aid in the adoption of the new nomenclature, all search tools can be used with both the current and pre-2010 allele designations. The pre-2010 nomenclature designations are only used where older reports or outputs have been made available for download.
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 ***
This site provides access to complete, annotated genomes from bacteria and archaea (present in the European Nucleotide Archive) through the Ensembl graphical user interface (genome browser). Ensembl Bacteria contains genomes from annotated INSDC records that are loaded into Ensembl multi-species databases, using the INSDC annotation import pipeline.
The Human Ageing Genomic Resources (HAGR) is a collection of databases and tools designed to help researchers study the genetics of human ageing using modern approaches such as functional genomics, network analyses, systems biology and evolutionary analyses.
The Cancer Cell Line Encyclopedia project is a collaboration between the Broad Institute, and the Novartis Institutes for Biomedical Research and its Genomics Institute of the Novartis Research Foundation to conduct a detailed genetic and pharmacologic characterization of a large panel of human cancer models, to develop integrated computational analyses that link distinct pharmacologic vulnerabilities to genomic patterns and to translate cell line integrative genomics into cancer patient stratification. The CCLE provides public access to genomic data, analysis and visualization for about 1000 cell lines.
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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.
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APID Interactomes is a database that provides a comprehensive collection of protein interactomes for more than 400 organisms based in the integration of known experimentally validated protein-protein physical interactions (PPIs). Construction of the interactomes is done with a methodological approach to report quality levels and coverage over the proteomes for each organism included. In this way, APID provides interactomes from specific organisms that in 25 cases have more than 500 proteins. As a whole APID includes a comprehensive compendium of 90,379 distinct proteins and 678,441 singular interactions. The analytical and integrative effort done in APID unifies PPIs from primary databases of molecular interactions (BIND, BioGRID, DIP, HPRD, IntAct, MINT) and also from experimentally resolved 3D structures (PDB) where more than two distinct proteins have been identified. In this way, 8,388 structures have been analyzed to find specific protein-protein interactions reported with details of their molecular interfaces. APID also includes a new data visualization web-tool that allows the construction of sub-interactomes using query lists of proteins of interest and the visual exploration of the corresponding networks, including an interactive selection of the properties of the interactions (i.e. the reliability of the "edges" in the network) and an interactive mapping of the functional environment of the proteins (i.e. the functional annotations of the "nodes" in the network).
The Ensembl genome annotation system, developed jointly by the EBI and the Wellcome Trust Sanger Institute, has been used for the annotation, analysis and display of vertebrate genomes since 2000. Since 2009, the Ensembl site has been complemented by the creation of five new sites, for bacteria, protists, fungi, plants and invertebrate metazoa, enabling users to use a single collection of (interactive and programatic) interfaces for accessing and comparing genome-scale data from species of scientific interest from across the taxonomy. In each domain, we aim to bring the integrative power of Ensembl tools for comparative analysis, data mining and visualisation across genomes of scientific interest, working in collaboration with scientific communities to improve and deepen genome annotation and interpretation.
The Ensembl project produces genome databases for vertebrates and other eukaryotic species. Ensembl is a joint project between the European Bioinformatics Institute (EBI) and the Wellcome Trust Sanger Institute (WTSI) to develop a software system that produces and maintains automatic annotation on selected genomes.The Ensembl project was started in 1999, some years before the draft human genome was completed. Even at that early stage it was clear that manual annotation of 3 billion base pairs of sequence would not be able to offer researchers timely access to the latest data. The goal of Ensembl was therefore to automatically annotate the genome, integrate this annotation with other available biological data and make all this publicly available via the web. Since the website's launch in July 2000, many more genomes have been added to Ensembl and the range of available data has also expanded to include comparative genomics, variation and regulatory data. Ensembl is a joint project between European Bioinformatics Institute (EBI), an outstation of the European Molecular Biology Laboratory (EMBL), and the Wellcome Trust Sanger Institute (WTSI). Both institutes are located on the Wellcome Trust Genome Campus in Hinxton, south of the city of Cambridge, United Kingdom.