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Found 253 result(s)
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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.
The Fungal Genetics Stock Center has preserved and distributed strains of genetically characterized fungi since 1960. The collection includes over 20,000 accessioned strains of classical and genetically engineered mutants of key model, human, and plant pathogenic fungi. These materials are distributed as living stocks to researchers around the world.
>>>>!!!!<<<< The Cancer Genomics Hub mission is now completed. The Cancer Genomics Hub was established in August 2011 to provide a repository to The Cancer Genome Atlas, the childhood cancer initiative Therapeutically Applicable Research to Generate Effective Treatments and the Cancer Genome Characterization Initiative. CGHub rapidly grew to be the largest database of cancer genomes in the world, storing more than 2.5 petabytes of data and serving downloads of nearly 3 petabytes per month. As the central repository for the foundational genome files, CGHub streamlined team science efforts as data became as easy to obtain as downloading from a hard drive. The convenient access to Big Data, and the collaborations that CGHub made possible, are now essential to cancer research. That work continues at the NCI's Genomic Data Commons. All files previously stored at CGHub can be found there. The Website for the Genomic Data Commons is here: https://gdc.nci.nih.gov/ >>>>!!!!<<<< The Cancer Genomics Hub (CGHub) is a secure repository for storing, cataloging, and accessing cancer genome sequences, alignments, and mutation information from the Cancer Genome Atlas (TCGA) consortium and related projects. Access to CGHub Data: All researchers using CGHub must meet the access and use criteria established by the National Institutes of Health (NIH) to ensure the privacy, security, and integrity of participant data. CGHub also hosts some publicly available data, in particular data from the Cancer Cell Line Encyclopedia. All metadata is publicly available and the catalog of metadata and associated BAMs can be explored using the CGHub Data Browser.
The Africa Health Research Institute (AHRI) has published its updated analytical datasets for 2016. The datasets cover socio-economic, education and employment information for individuals and households in AHRI’s population research area in rural northern KwaZulu-Natal. The datasets also include details on the migration patterns of the individuals and households who migrated into and out of the surveillance area as well as data on probable causes of death for individuals who passed away. Data collection for the 2016 individual interviews – which involves a dried blood spot sample being taken – is still in progress, and therefore datasets on HIV status and General Health only go up to 2015 for now. Over the past 16 years researchers have developed an extensive longitudinal database of demographic, social, economic, clinical and laboratory information about people over the age of 15 living in the AHRI population research area. During this time researchers have followed more than 160 000 people, of which 92 000 are still in the programme.
Human Protein Reference Database (HPRD) has been established by a team of biologists, bioinformaticists and software engineers. This is a joint project between the PandeyLab at Johns Hopkins University, and Institute of Bioinformatics, Bangalore. HPRD is a definitive repository of human proteins. This database should serve as a ready reckoner for researchers in their quest for drug discovery, identification of disease markers and promote biomedical research in general. Human Proteinpedia (www.humanproteinpedia.org) is its associated data portal.
CalSurv is a comprehensive information on West Nile virus, plague, malaria, Lyme disease, trench fever and other vectorborne diseases in California — where they are, where they’ve been, where they may be headed and what new diseases may be emerging.The CalSurv Web site serves as a portal or a single interface to all surveillance-related Web sites in California.
CDC.gov is the Centers for Disease Control and Prevention primary online communication channel. CDC.gov provides users with credible, reliable health information on Data and Statistics, Diseases and Conditions, Emergencies and Disasters, Environmental Health, Healthy Living, Injury, Violence and Safety,Life Stages and Populations, Travelers' Health, Workplace Safety and Health
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>>>!!!<<< The NCI Cancer Models Database, caMOD, was retired on December 24, 2015. Information about many of the mouse models hosted in caMOD was obtained from the Jackson Laboratory Mouse Tumor Biology (MTB) Database and can be accessed through that resource http://tumor.informatics.jax.org/mtbwi/index.do . See caMOD Retirement Announcement https://wiki.nci.nih.gov/display/caMOD/caMOD+Retirement+Announcement >>>>!!<<< Query the Cancer Models database for models submitted by fellow researchers. Retrieve information about the making of models, their genetic description, histopathology, derived cell lines, associated images, carcinogenic agents, and therapeutic trials. Links to associated publications and other resources are provided.
>>> !!! the repository is offline !!! <<< More information see: https://dknet.org/about/NURSA_Archive All NURSA-biocurated transcriptomic datasets have been preserved for data mining in SPP through an enhanced and expanded version of Transcriptomine named Ominer. To access these datasets, dkNET provides users with the information of 527 transcriptomic datasets that contain data related to nuclear receptors and nuclear receptor coregulators in the NURSA Datasets table view and redirects users to the current SPP dataset page. Once users find the specific dataset of research interest, users can download the dataset by clicking DOI and then clicking the Download Dataset button at the Signaling Pathways Project webpage. See https://www.re3data.org/repository/r3d100013650
<<<!!!<<< 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.
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The Centre for Applied Genomics hosts a variety of databases related to ongoing supported projects. Curation of these databases is performed in-house by TCAG Bioinformatics staff. The Autism Chromosome Rearrangement Database, The Cystic Fibrosis Mutation Database, TThe Lafora Progressive Myoclonus Epilepsy Mutation and Polymorphism Database are included. Large Scale Genomics Research resources include, the Database of Genomic Variants, The Chromosome 7 Annotation Project, The Human Genome Segmental Duplication Database, and the Non-Human Segmental Duplication Database
>>>!!!<<< Noticed 26.08.2020: The NCI CBIIT instance of the CGAP no longer exist on this website. The Mitelman Database of Chromosome Aberrations and Gene Fusions in Cancer has a new home at the NCI-funded Institute for Systems Biology Cancer Genomics Cloud available at the following location: https://mitelmandatabase.isb-cgc.org >>>!!!<<<
GeneWeaver combines cross-species data and gene entity integration, scalable hierarchical analysis of user data with a community-built and curated data archive of gene sets and gene networks, and tools for data driven comparison of user-defined biological, behavioral and disease concepts. Gene Weaver allows users to integrate gene sets across species, tissue and experimental platform. It differs from conventional gene set over-representation analysis tools in that it allows users to evaluate intersections among all combinations of a collection of gene sets, including, but not limited to annotations to controlled vocabularies. There are numerous applications of this approach. Sets can be stored, shared and compared privately, among user defined groups of investigators, and across all users.
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With its “Blood Donor BIOBANK”, the Bavarian Red Cross (BRK) Blood Donor Service offers a unique and innovative resource for biomarker research: the world’s first blood donor based biobank. Biobanks as collections of biological material together with associated medical data open new possibilities for the development of new targeted diagnostics and therapies. The BRK Blood Donor Service maintains a unique collection of over 3 million blood samples, making it one of the largest sample collections worldwide. Every working day 2,000 new samples are added to the collection.
The Cancer Immunome Database (TCIA) provides results of comprehensive immunogenomic analyses of next generation sequencing data (NGS) data for 20 solid cancers from The Cancer Genome Atlas (TCGA) and other datasource. The Cancer Immunome Atlas (TCIA) was developed and is maintained at the Division of Bioinformatics (ICBI). The database can be queried for the gene expression of specific immune-related gene sets, cellular composition of immune infiltrates (characterized using gene set enrichment analyses and deconvolution), neoantigens and cancer-germline antigens, HLA types, and tumor heterogeneity (estimated from cancer cell fractions). Moreover it provides survival analyses for different types immunological parameters. TCIA will be constantly updated with new data and results.
BEI Resources was established by the National Institute of Allergy and Infectious Diseases (NIAID) to provide reagents, tools and information for studying Category A, B, and C priority pathogens, emerging infectious disease agents, non-pathogenic microbes and other microbiological materials of relevance to the research community. BEI Resources acquires authenticates, and produces reagents that scientists need to carry out basic research and develop improved diagnostic tests, vaccines, and therapies. By centralizing these functions within BEI Resources, access to and use of these materials in the scientific community is monitored and quality control of the reagents is assured
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The Small Molecule Pathway Database (SMPDB) contains small molecule pathways found in humans, which are presented visually. All SMPDB pathways include information on the relevant organs, subcellular compartments, protein cofactors, protein locations, metabolite locations, chemical structures and protein quaternary structures. Accompanying data includes detailed descriptions and references, providing an overview of the pathway, condition or processes depicted in each diagram.
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The Biobanque québécoise de la COVID-19 (BQC19) is a pan-provincial initiative that collects, stores and shares data and blood samples from COVID-19 patients, both severe and non-severe cases and control cases, in an effort to respond effectively to the public health challenges posed by the pandemic. BQC19 believes that better understanding the disease will help society in returning to social activities and in preparing for future pandemics. It sees access to high-quality samples and data as essential in fulfilling research and works to bring about national and international research collaborations.
The CONP portal is a web interface for the Canadian Open Neuroscience Platform (CONP) to facilitate open science in the neuroscience community. CONP simplifies global researcher access and sharing of datasets and tools. The portal internalizes the cycle of a typical research project: starting with data acquisition, followed by processing using already existing/published tools, and ultimately publication of the obtained results including a link to the original dataset. From more information on CONP, please visit https://conp.ca
The Protein Data Bank (PDB) is an archive of experimentally determined three-dimensional structures of biological macromolecules that serves a global community of researchers, educators, and students. The data contained in the archive include atomic coordinates, crystallographic structure factors and NMR experimental data. Aside from coordinates, each deposition also includes the names of molecules, primary and secondary structure information, sequence database references, where appropriate, and ligand and biological assembly information, details about data collection and structure solution, and bibliographic citations. The Worldwide Protein Data Bank (wwPDB) consists of organizations that act as deposition, data processing and distribution centers for PDB data. Members are: RCSB PDB (USA), PDBe (Europe) and PDBj (Japan), and BMRB (USA). The wwPDB's mission is to maintain a single PDB archive of macromolecular structural data that is freely and publicly available to the global community.
In 2003, the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) at NIH established Data, Biosample, and Genetic Repositories to increase the impact of current and previously funded NIDDK studies by making their data and biospecimens available to the broader scientific community. These Repositories enable scientists not involved in the original study to test new hypotheses without any new data or biospecimen collection, and they provide the opportunity to pool data across several studies to increase the power of statistical analyses. In addition, most NIDDK-funded studies are collecting genetic biospecimens and carrying out high-throughput genotyping making it possible for other scientists to use Repository resources to match genotypes to phenotypes and to perform informative genetic analyses.
Addgene archives and distributes plasmids for researchers around the globe. They are working with thousands of laboratories to assemble a high-quality library of published plasmids for use in research and discovery. By linking plasmids with articles, scientists can always find data related to the materials they request.