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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.
<<<!!!<<< 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.
ArrayExpress is one of the major international repositories for high-throughput functional genomics data from both microarray and high-throughput sequencing studies, many of which are supported by peer-reviewed publications. Data sets are submitted directly to ArrayExpress and curated by a team of specialist biological curators. In the past (until 2018) datasets from the NCBI Gene Expression Omnibus database were imported on a weekly basis. Data is collected to MIAME and MINSEQE standards.
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.
The Yeast Resource Center Public Image Repository is a database of fluorescent microscopy images and their associated metadata/experimental parameters. The images depict the localization, co-localization and FRET (fluorescence energy transfer) of proteins in cells, particularly in the budding yeast Saccharomyces cerevisiae as a model organism. Users may download the entire datasets to improve their research.
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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.
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.