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Found 36 result(s)
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.
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>>>!!!<<< The repository is no longer available. >>>!!!<<< Indian Genetic Disease Database (IGDD) is an initiative of CSIR Indian Institute of Chemical Biology. It is supported by Council of Scientific and Industrial Research (CSIR) and Department of Biotechnology (DBT) of India. The Indian people represent one-sixth of the world population and consists of a ethnically, geographically, and genetically diverse population. In some communities the ratio of genetic disorder is relatively high due to consanguineous marriage practiced in the community. This database has been created to keep track of mutations in the causal genes for genetic diseases common in India and help the physicians, geneticists, and other professionals retrieve and use the information for the benefit of the public. The database includes scientific information about these genetic diseases and disabilities, but also statistical information about these diseases in today's society. Data is categorized by body part affected and then by title of the disease.
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 Autism Chromosome Rearrangement Database is a collection of hand curated breakpoints and other genomic features, related to autism, taken from publicly available literature: databases and unpublished data. The database is continuously updated with information from in-house experimental data as well as data from published research studies.
The HUGO Gene Nomenclature Committee (HGNC) assigned unique gene symbols and names to over 35,000 human loci, of which around 19,000 are protein coding. This curated online repository of HGNC-approved gene nomenclature and associated resources includes links to genomic, proteomic and phenotypic information, as well as dedicated gene family pages.
<<<!!!<<< 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. >>>!!!>>>
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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iDog, an integrated resource for domestic dog (Canis lupus familiaris) and wild canids, provides the worldwide dog research community a variety of data services. This includes Genes, Genomes, SNPs, Breed/Disease Traits, Gene Expressions, Single Cell, Dog-Human Homolog Diseases and Literatures. In addition, iDog provides Online tools for performing genomic data visualization and analyses.
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).
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.
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During cell cycle, numerous proteins temporally and spatially localized in distinct sub-cellular regions including centrosome (spindle pole in budding yeast), kinetochore/centromere, cleavage furrow/midbody (related or homolog structures in plants and budding yeast called as phragmoplast and bud neck, respectively), telomere and spindle spatially and temporally. These sub-cellular regions play important roles in various biological processes. In this work, we have collected all proteins identified to be localized on kinetochore, centrosome, midbody, telomere and spindle from two fungi (S. cerevisiae and S. pombe) and five animals, including C. elegans, D. melanogaster, X. laevis, M. musculus and H. sapiens based on the rationale of "Seeing is believing" (Bloom K et al., 2005). Through ortholog searches, the proteins potentially localized at these sub-cellular regions were detected in 144 eukaryotes. Then the integrated and searchable database MiCroKiTS - Midbody, Centrosome, Kinetochore, Telomere and Spindle has been established.
<<<!!!<<< 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.
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.
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CTD is a robust, publicly available database that aims to advance understanding about how environmental exposures affect human health. It provides manually curated information about chemical–gene/protein interactions, chemical–disease and gene–disease relationships. These data are integrated with functional and pathway data to aid in development of hypotheses about the mechanisms underlying environmentally influenced diseases. We also have additional ongoing projects involving manual curation of exposome data and chemical–phenotype relationships to help identify pre–disease biomarkers resulting from environmental exposures. The initial release of CTD was on November 12, 2004. We’re grateful to our strong community support and encourage you to give us feedback so we can continue to evolve with your research needs.
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A small genotype data repository containing data used in recent papers from the Estonian Biocentre. Most of the data pertains to human population genetics. PDF files of the papers are also freely available.
EMAGE (e-Mouse Atlas of Gene Expression) is an online biological database of gene expression data in the developing mouse (Mus musculus) embryo. The data held in EMAGE is spatially annotated to a framework of 3D mouse embryo models produced by EMAP (e-Mouse Atlas Project). These spatial annotations allow users to query EMAGE by spatial pattern as well as by gene name, anatomy term or Gene Ontology (GO) term. EMAGE is a freely available web-based resource funded by the Medical Research Council (UK) and based at the MRC Human Genetics Unit in the Institute of Genetics and Molecular Medicine, Edinburgh, UK.
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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.
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>>>!!! <<< 2021-09-01: repository is offline >>>!!!<<< Background: Many studies have been conducted to detect quantitative trait loci (QTL) in dairy cattle. However, these studies are diverse in terms of their differing resource populations, marker maps, phenotypes, etc, and one of the challenges is to be able to synthesise this diverse information. This web page has been constructed to provide an accessible database of studies, providing a summary of each study, facilitating an easier comparison across studies. However, it also highlights the need for uniform reporting of results of studies, to facilitate more direct comparisons being made. Description: Studies recorded in this database include complete and partial genome scans, single chromosome scans, as well as fine mapping studies, and contain all known reports that were published in peer-reviewed journals and readily available conference proceedings, initially up to April 2005. However, this data base is being added to, as indicated by the last web update. Note that some duplication of results will occur, in that there may be a number of reports on the same resource population, but utilising different marker densities or different statistical methodologies. The traits recorded in this map are milk yield, milk composition (protein yield, protein %, fat yield, fat %), and somatic cell score (SCS).
The Human Ageing Genomic Resources (HAGR) is a collection of databases and tools designed to help researchers study the genetics of human ageing using modern approaches such as functional genomics, network analyses, systems biology and evolutionary analyses.
PeanutBase is a peanut community resource providing genetic, genomic, gene function, and germplasm data to support peanut breeding and molecular research. This includes molecular markers, genetic maps, QTL data, genome assemblies, germplasm records, and traits. Data is curated from literature and submitted directly by researchers. Funding for PeanutBase is provided by the Peanut Foundation with in-kind contributions from the USDA-ARS.