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Found 29 result(s)
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We are a leading international centre for genomics and bioinformatics research. Our mandate is to advance knowledge about cancer and other diseases, to improve human health through disease prevention, diagnosis and therapeutic approaches, and to realize the social and economic benefits of genomics research.
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.
MGI is the international database resource for the laboratory mouse, providing integrated genetic, genomic, and biological data to facilitate the study of human health and disease. The projects contributing to this resource are: Mouse Genome Database (MGD) Project, Gene Expression Database (GXD) Project, Mouse Tumor Biology (MTB) Database Project, Gene Ontology (GO) Project at MGI, MouseMine Project, MouseCyc Project at MGI
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CBS offers Comprehensive public databases of DNA- and protein sequences, macromolecular structure, g ene and protein expression levels, pathway organization and cell signalling, have been established to optimise scientific exploitation of the explosion of data within biology. Unlike many other groups in the field of biomolecular informatics, Center for Biological Sequence Analysis directs its research primarily towards topics related to the elucidation of the functional aspects of complex biological mechanisms. Among contemporary bioinformatics concerns are reliable computational interpretation of a wide range of experimental data, and the detailed understanding of the molecular apparatus behind cellular mechanisms of sequence information. By exploiting available experimental data and evidence in the design of algorithms, sequence correlations and other features of biological significance can be inferred. In addition to the computational research the center also has experimental efforts in gene expression analysis using DNA chips and data generation in relation to the physical and structural properties of DNA. In the last decade, the Center for Biological Sequence Analysis has produced a large number of computational methods, which are offered to others via WWW servers.
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.
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.
BiGG is a knowledgebase of Biochemically, Genetically and Genomically structured genome-scale metabolic network reconstructions. BiGG integrates several published genome-scale metabolic networks into one resource with standard nomenclature which allows components to be compared across different organisms. BiGG can be used to browse model content, visualize metabolic pathway maps, and export SBML files of the models for further analysis by external software packages. Users may follow links from BiGG to several external databases to obtain additional information on genes, proteins, reactions, metabolites and citations of interest.
This Web resource provides data and information relevant to SARS coronavirus. It includes links to the most recent sequence data and publications, to other SARS related resources, and a pre-computed alignment of genome sequences from various isolates. The genome of SARS-CoV consists of a single, positive-strand RNA that is approximately 29,700 nucleotides long. The overall genome organization of SARS-CoV is similar to that of other coronaviruses. The reference genome includes 13 genes, which encode at least 14 proteins. Two large overlapping reading frames (ORFs) encompass 71% of the genome. The remainder has 12 potential ORFs, including genes for structural proteins S (spike), E (small envelope), M (membrane), and N (nucleocapsid). Other potential ORFs code for unique putative SARS-CoV-specific polypeptides that lack obvious sequence similarity to known proteins.
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 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.
TriTrypDB is an integrated genomic and functional genomic database for pathogens of the family Trypanosomatidae, including organisms in both Leishmania and Trypanosoma genera. TriTrypDB and its continued development are possible through the collaborative efforts between EuPathDB, GeneDB and colleagues at the Seattle Biomedical Research Institute (SBRI).
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.
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The Taenia solium genome project is a whole genome sequencing project of the parasite Taenia solium, the causal agent of human and porcine cysticercosis; a disease that is still a public health problem of relevance in Mexico. It is being carried out by a consortium of scientists belonging to diverse institutions of the Universidad Nacional Autónoma de México (UNAM, the National Autonomous University of Mexico).
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Introduction of genome-scale metabolic network: The completion of genome sequencing and subsequent functional annotation for a great number of species enables the reconstruction of genome-scale metabolic networks. These networks, together with in silico network analysis methods such as the constraint based methods (CBM) and graph theory methods, can provide us systems level understanding of cellular metabolism. Further more, they can be applied to many predictions of real biological application such as: gene essentiality analysis, drug target discovery and metabolic engineering
ASAP (a systematic annotation package for community analysis of genomes) is a relational database and web interface developed to store, update and distribute genome sequence data and gene expression data collected by or in collaboration with researchers at the University of Wisconsin - Madison. ASAP was designed to facilitate ongoing community annotation of genomes and to grow with genome projects as they move from the preliminary data stage through post-sequencing functional analysis. The ASAP database includes multiple genome sequences at various stages of analysis, and gene expression data from preliminary experiments.
MetaCyc is a curated database of experimentally elucidated metabolic pathways from all domains of life. MetaCyc contains pathways involved in both primary and secondary metabolism, as well as associated metabolites, reactions, enzymes, and genes. The goal of MetaCyc is to catalog the universe of metabolism by storing a representative sample of each experimentally elucidated pathway. MetaCyc applications include: Online encyclopedia of metabolism, Prediction of metabolic pathways in sequenced genomes, Support metabolic engineering via enzyme database, Metabolite database aids. metabolomics research.
The mission of the Influenza Research Database (IRD) is to provide a resource for the influenza virus research community that will facilitate an understanding of the influenza virus and how it interacts with the host organism, leading to new treatments and preventive actions. This resource will contain avian and non-human mammalian influenza surveillance data, human clinical data associated with virus extracts, phenotypic characteristics of viruses isolated from extracts, and all genomic and proteomic data available in public repositories for influenza viruses.