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Online Mendelian Inheritance in Animals (OMIA) is a catalogue/compendium of inherited disorders, other (single-locus) traits, and genes in 218 animal species (other than human and mouse and rats, which have their own resources) authored by Professor Frank Nicholas of the University of Sydney, Australia, with help from many people over the years. OMIA information is stored in a database that contains textual information and references, as well as links to relevant PubMed and Gene records at the NCBI, and to OMIM and Ensembl.
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. >>>!!!>>>
<<<!!!<<< 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.
MicrosporidiaDB belongs to the EuPathDB family of databases and is an integrated genomic and functional genomic database for the phylum Microsporidia. In its first iteration (released in early 2010), MicrosporidiaDB contains the genomes of two Encephalitozoon species (see below). MicrosporidiaDB integrates whole genome sequence and annotation and will rapidly expand to include experimental data and environmental isolate sequences provided by community researchers. The database includes supplemental bioinformatics analyses and a web interface for data-mining.
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.
The DNA Bank Network was established in spring 2007 and was funded until 2011 by the German Research Foundation (DFG). The network was initiated by GBIF Germany (Global Biodiversity Information Facility). It offers a worldwide unique concept. DNA bank databases of all partners are linked and are accessible via a central web portal, providing DNA samples of complementary collections (microorganisms, protists, plants, algae, fungi and animals). The DNA Bank Network was one of the founders of the Global Genome Biodiversity Network (GGBN) and is fully merged with GGBN today. GGBN agreed on using the data model proposed by the DNA Bank Network. The Botanic Garden and Botanical Museum Berlin-Dahlem (BGBM) hosts the technical secretariat of GGBN and its virtual infrastructure. The main focus of the DNA Bank Network is to enhance taxonomic, systematic, genetic, conservation and evolutionary studies by providing: • high quality, long-term storage of DNA material on which molecular studies have been performed, so that results can be verified, extended, and complemented, • complete on-line documentation of each sample, including the provenance of the original material, the place of voucher deposit, information about DNA quality and extraction methodology, digital images of vouchers and links to published molecular data if available.
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.