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Found 28 result(s)
dbEST is a division of GenBank that contains sequence data and other information on "single-pass" cDNA sequences, or "Expressed Sequence Tags", from a number of organisms. Expressed Sequence Tags (ESTs) are short (usually about 300-500 bp), single-pass sequence reads from mRNA (cDNA). Typically they are produced in large batches. They represent a snapshot of genes expressed in a given tissue and/or at a given developmental stage. They are tags (some coding, others not) of expression for a given cDNA library. Most EST projects develop large numbers of sequences. These are commonly submitted to GenBank and dbEST as batches of dozens to thousands of entries, with a great deal of redundancy in the citation, submitter and library information. To improve the efficiency of the submission process for this type of data, we have designed a special streamlined submission process and data format. dbEST also includes sequences that are longer than the traditional ESTs, or are produced as single sequences or in small batches. Among these sequences are products of differential display experiments and RACE experiments. The thing that these sequences have in common with traditional ESTs, regardless of length, quality, or quantity, is that there is little information that can be annotated in the record. If a sequence is later characterized and annotated with biological features such as a coding region, 5'UTR, or 3'UTR, it should be submitted through the regular GenBank submissions procedure (via BankIt or Sequin), even if part of the sequence is already in dbEST. dbEST is reserved for single-pass reads. Assembled sequences should not be submitted to dbEST. GenBank will accept assembled EST submissions for the forthcoming TSA (Transcriptome Shotgun Assembly) division. The individual reads which make up the assembly should be submitted to dbEST, the Trace archive or the Short Read Archive (SRA) prior to the submission of the assemblies.
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.
NCBI Datasets is a continually evolving platform designed to provide easy and intuitive access to NCBI’s sequence data and metadata. NCBI Datasets is part of the NIH Comparative Genomics Resource (CGR). CGR facilitates reliable comparative genomics analyses for all eukaryotic organisms through an NCBI Toolkit and community collaboration.
IntAct provides a freely available, open source database system and analysis tools for molecular interaction data. All interactions are derived from literature curation or direct user submissions and are freely available.
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 DIP database catalogs experimentally determined interactions between proteins. It combines information from a variety of sources to create a single, consistent set of protein-protein interactions. The data stored within the DIP database were curated, both, manually by expert curators and also automatically using computational approaches that utilize the the knowledge about the protein-protein interaction networks extracted from the most reliable, core subset of the DIP data. Please, check the reference page to find articles describing the DIP database in greater detail. The Database of Ligand-Receptor Partners (DLRP) is a subset of DIP (Database of Interacting Proteins). The DLRP is a database of protein ligand and protein receptor pairs that are known to interact with each other. By interact we mean that the ligand and receptor are members of a ligand-receptor complex and, unless otherwise noted, transduce a signal. In some instances the ligand and/or receptor may form a heterocomplex with other ligands/receptors in order to be functional. We have entered the majority of interactions in DLRP as full DIP entries, with links to references and additional information
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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.
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<<<!!!<<< 2017-06-02: We recently suffered a server failure and are working to bring the full ORegAnno website back online. In the meantime, you may download the complete database here: http://www.oreganno.org/dump/ ; Data are also available through UCSC Genome Browser (e.g., hg38 -> Regulation -> ORegAnno) https://genome.ucsc.edu/cgi-bin/hgTrackUi?hgsid=686342163_2it3aVMQVoXWn0wuCjkNOVX39wxy&c=chr1&g=oreganno >>>!!!>>> The Open REGulatory ANNOtation database (ORegAnno) is an open database for the curation of known regulatory elements from scientific literature. Annotation is collected from users worldwide for various biological assays and is automatically cross-referenced against PubMED, Entrez Gene, EnsEMBL, dbSNP, the eVOC: Cell type ontology, and the Taxonomy database, where appropriate, with information regarding the original experimentation performed (evidence). ORegAnno further provides an open validation process for all regulatory annotation in the public domain. Assigned validators receive notification of new records in the database and are able to cross-reference the citation to ensure record integrity. Validators have the ability to modify any record (deprecating the old record and creating a new one) if an error is found. Further, any contributor to the database can comment on any annotation by marking errors, or adding special reports into function as they see fit. These features of ORegAnno ensure that the collection is of the highest quality and uniquely provides a dynamic view of our changing understanding of gene regulation in the various genomes.
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***
<<<!!!<<< This repository is no longer available>>>!!!>>>. Although the web pages are no longer available, you will still be able to download the final UniGene builds as static content from the FTP site https://ftp.ncbi.nlm.nih.gov/repository/UniGene/. You will also be able to match UniGene cluster numbers to Gene records by searching Gene with UniGene cluster numbers. For best results, restrict to the “UniGene Cluster Number” field rather than all fields in Gene. For example, a search with Mm.2108[UniGene Cluster Number] finds the mouse transthyretin Gene record (Ttr). You can use the advanced search page https://www.ncbi.nlm.nih.gov/gene/advanced to help construct these searches. Keep in mind that the Gene record contains selected Reference Sequences and GenBank mRNA sequences rather than the larger set of expressed sequences in the UniGene cluster.
InnateDB is a publicly available database of the genes, proteins, experimentally-verified interactions and signaling pathways involved in the innate immune response of humans, mice and bovines to microbial infection. The database captures an improved coverage of the innate immunity interactome by integrating known interactions and pathways from major public databases together with manually-curated data into a centralised resource. The database can be mined as a knowledgebase or used with our integrated bioinformatics and visualization tools for the systems level analysis of the innate immune response.
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.
<<<!!!<<< See UniProt entry https://www.re3data.org/repository/r3d100011521 >>>!!!>>> UniProtKB/Swiss-Prot is the manually annotated and reviewed section of the UniProt Knowledgebase (UniProtKB). It is a high quality annotated and non-redundant protein sequence database, which brings together experimental results, computed features and scientific conclusions. Since 2002, it is maintained by the UniProt consortium and is accessible via the UniProt website.
>>>!!! <<< The Epigenomics database was retired on June 1, 2016. All epigenomics data are available in our GEO resource https://www.ncbi.nlm.nih.gov/geo >>> !!! <<< The Epigenomics database provides genomics maps of stable and reprogrammable nuclear changes that control gene expression and influence health. Users can browse current epigenomic experiments as well as search, compare and browse samples from multiple biological sources in gene-specific contexts. Many epigenomes contain modifications with histone marks, DNA methylation and chromatin structure activity. NCBI Epigenomics database contains datasets from the NIH Roadmap Epigenomics Project.
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<<<!!!<<< Genome data generated by BC Genome Sciences Centre is no longer available through this site as it is regularly deposited into controlled data repositories such as the European Genome Phenome Archive (EGA); ICGC (International Cancer Genome Consortium) and the Genome Data Commons (GDC) >>>!!!>>> Mapping, copy number analysis, sequence and gene expression data generated by the High Resolution Analysis of Follicular Lymphoma Genomes project. The data will be available for 24 patients with follicular lymphoma. All data will be made as widely and freely available as possible while safeguarding the privacy of participants, and protecting confidential and proprietary data.The data from this project will be submitted to public genomic data sources. These sources will be listed on this web site as the data becomes available in these external data sources.
In response to emerging pathogens, LabKey launched the Open Research Portal in 2016 to help facilitate collaborative research. It was initially created as a platform for investigators to make Zika research data, commentary and results publicly available in real-time. It now includes other viruses like SARS-CoV-2 where there is a compelling need for real-time data sharing. Projects are freely available to researchers. If you are interested in sharing real-time data through the portal, please contact LabKey to get started.
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.
The Barcode of Life Data Systems (BOLD) provides DNA barcode data. BOLD's online workbench supports data validation, annotation, and publication for specimen, distributional, and molecular data. The platform consists of four main modules: a data portal, a database of barcode clusters, an educational portal, and a data collection workbench. BOLD is the go-to site for DNA-based identification. As the central informatics platform for DNA barcoding, BOLD plays a crucial role in assimilating and organizing data gathered by the international barcode research community. Two iBOL (International Barcode of Life) Working Groups are supporting the ongoing development of BOLD.
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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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.