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Found 44 result(s)
The tree of life links all biodiversity through a shared evolutionary history. This project will produce the first online, comprehensive first-draft tree of all 1.8 million named species, accessible to both the public and scientific communities. Assembly of the tree will incorporate previously-published results, with strong collaborations between computational and empirical biologists to develop, test and improve methods of data synthesis. This initial tree of life will not be static; instead, we will develop tools for scientists to update and revise the tree as new data come in. Early release of the tree and tools will motivate data sharing and facilitate ongoing synthesis of knowledge.
DNASU is a central repository for plasmid clones and collections. Currently we store and distribute over 200,000 plasmids including 75,000 human and mouse plasmids, full genome collections, the protein expression plasmids from the Protein Structure Initiative as the PSI: Biology Material Repository (PSI : Biology-MR), and both small and large collections from individual researchers. We are also a founding member and distributor of the ORFeome Collaboration plasmid collection.
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The Health Atlas is an alliance of medical ontologists, medical systems biologists and clinical trials groups to design and implement a multi-functional and quality-assured atlas. It provides models, data and metadata on specific use cases from medical research projects from the partner institutions.
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.
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
IntEnz contains the recommendation of the Nomenclature Committee of the International Union of Biochemistry and Molecular Biology on the nomenclature and classification of enzyme-catalyzed reactions. Users can browse by enzyme classification or use advanced search options to search enzymes by class, subclass and sub-subclass information.
The Brain Transcriptome Database (BrainTx) project aims to create an integrated platform to visualize and analyze our original transcriptome data and publicly accessible transcriptome data related to the genetics that underlie the development, function, and dysfunction stages and states of the brain.
Clinical Genomic Database (CGD) is a manually curated database of conditions with known genetic causes, focusing on medically significant genetic data with available interventions.
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The DrugBank database is a unique bioinformatics and cheminformatics resource that combines detailed drug (i.e. chemical, pharmacological and pharmaceutical) data with comprehensive drug target (i.e. sequence, structure, and pathway) information. The latest release of DrugBank (version 5.1.1, released 2018-07-03) contains 11,881 drug entries including 2,526 approved small molecule drugs, 1,184 approved biotech (protein/peptide) drugs, 129 nutraceuticals and over 5,751 experimental drugs. Additionally, 5,132 non-redundant protein (i.e. drug target/enzyme/transporter/carrier) sequences are linked to these drug entries. Each DrugCard entry contains more than 200 data fields with half of the information being devoted to drug/chemical data and the other half devoted to drug target or protein data.
Candida Genome Database, a resource for genomic sequence data and gene and protein information for Candida albicans and related species. CGD is based on the Saccharomyces Genome Database. The Candida Genome Database (CGD) provides online access to genomic sequence data and manually curated functional information about genes and proteins of the human pathogen Candida albicans and related species. C. albicans is the best studied of the human fungal pathogens. It is a common commensal organism of healthy individuals, but can cause debilitating mucosal infections and life-threatening systemic infections, especially in immunocompromised patients. C. albicans also serves as a model organism for the study of other fungal pathogens.
Neuroimaging Tools and Resources Collaboratory (NITRC) is currently a free one-stop-shop environment for science researchers that need resources such as neuroimaging analysis software, publicly available data sets, and computing power. Since its debut in 2007, NITRC has helped the neuroscience community to use software and data produced from research that, before NITRC, was routinely lost or disregarded, to make further discoveries. NITRC provides free access to data and enables pay-per-use cloud-based access to unlimited computing power, enabling worldwide scientific collaboration with minimal startup and cost. With NITRC and its components—the Resources Registry (NITRC-R), Image Repository (NITRC-IR), and Computational Environment (NITRC-CE)—a researcher can obtain pilot or proof-of-concept data to validate a hypothesis for a few dollars.
STOREDB is a platform for the archiving and sharing of primary data and outputs of all kinds, including epidemiological and experimental data, from research on the effects of radiation. It also provides a directory of bioresources and databases containing information and materials that investigators are willing to share. STORE supports the creation of a radiation research commons.
<<<!!!<<< 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.
<<<!!!<<< This repository is no longer available. >>>!!!>>> BioVeL is a virtual e-laboratory that supports research on biodiversity issues using large amounts of data from cross-disciplinary sources. BioVeL supports the development and use of workflows to process data. It offers the possibility to either use already made workflows or create own. BioVeL workflows are stored in MyExperiment - Biovel Group http://www.myexperiment.org/groups/643/content. They are underpinned by a range of analytical and data processing functions (generally provided as Web Services or R scripts) to support common biodiversity analysis tasks. You can find the Web Services catalogued in the BiodiversityCatalogue.
Complete Genomics provides free public access to a variety of whole human genome data sets generated from Complete Genomics’ sequencing service. The research community can explore and familiarize themselves with the quality of these data sets, review the data formats provided from our sequencing service, and augment their own research with additional summaries of genomic variation across a panel of diverse individuals. The quality of these data sets is representative of what a customer can expect to receive for their own samples. This public genome repository comprises genome results from both our Standard Sequencing Service (69 standard, non-diseased samples) and the Cancer Sequencing Service (two matched tumor and normal sample pairs). In March 2013 Complete Genomics was acquired by BGI-Shenzhen , the world’s largest genomics services company. BGI is a company headquartered in Shenzhen, China that provides comprehensive sequencing and bioinformatics services for commercial science, medical, agricultural and environmental applications. Complete Genomics is now focused on building a new generation of high-throughput sequencing technology and developing new and exciting research, clinical and consumer applications.
SoyBase is a professionally curated repository for genetics, genomics and related data resources for soybean. It contains current genetic, physical and genomic sequence maps integrated with qualitative and quantitative traits. SoyBase includes annotated "Williams 82" genomic sequence and associated data mining tools. The repository maintains controlled vocabularies for soybean growth, development, and traits that are linked to more general plant ontologies.
The Electron Microscopy Data Bank (EMDB) is a public repository for electron microscopy density maps of macromolecular complexes and subcellular structures. It covers a variety of techniques, including single-particle analysis, electron tomography, and electron (2D) crystallography.
The Malaria Atlas Project (MAP) brings together researchers based around the world with expertise in a wide range of disciplines from public health to mathematics, geography and epidemiology. We work together to generate new and innovative methods of mapping malaria risk. Ultimately our goal is to produce a comprehensive range of maps and estimates that will support effective planning of malaria control at national and international scales.
<<<!!!<<< This site is no longer maintained and is provided for reference only. Some functionality or links may not work. For all enquiries please contact the Ensembl Helpdesk http://www.ensembl.org/Help/Contact >>>!!!>>> PhytoPath is a new bioinformatics resource that integrates genome-scale data from important plant pathogen species with literature-curated information about the phenotypes of host infection. Using the Ensembl Genomes browser, it provides access to complete genome assembly and gene models of priority crop and model-fungal, oomycete and bacterial phytopathogens. PhytoPath also links genes to disease progression using data from the curated PHI-base resource. PhytoPath portal is a joint project bringing together Ensembl Genomes with PHI-base, a community-curated resource describing the role of genes in pathogenic infection. PhytoPath provides access to genomic and phentoypic data from fungal and oomycete plant pathogens, and has enabled a considerable increase in the coverage of phytopathogen genomes in Ensembl Fungi and Ensembl Protists. PhytoPath also provides enhanced searching of the PHI-base resource as well as the fungi and protists in Ensembl Genomes.
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This study assessed differences in avian biodiversity across different forest age-classes, including mature stands (> 100 years), in a managed, mixed-species eucalypt forest located in Gippsland, south-eastern Australia. Avian surveys and detailed habitat measurements were initially carried out in 50 two hectare stands ranging in age from 100 years. Extensive wildfire which occurred during the study reduced the number of sites to 28 (seven in each of four age classes) upon which analyses and inferences were made. Mature vegetation (> 100 years) had the greatest richness, abundance and biomass of birds. Key ecological resources, such as tree-hollows for nesting, generally occurred mostly in stands > 60 years. There were quantum increases in all measures of avian biodiversity in mature stands (> 100 years). The visualisation of the survey data is part of an interoperable web-GIS maintained by the Centre for eResearch and Digital Innovation (CeRDI) at Federation University Australia (FedUni).
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<<<!!!<<< 2019-12-23: the repository is offline >>>!!!>>> 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
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CORUM is a manually curated dataset of mammalian protein complexes. Annotation of protein complexes includes protein complex composition and other valuable information such as method of purification, cellular function of complexes or involvement in diseases.