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Found 116 result(s)
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Silkworm Pathogen Database (SilkPathDB) is a comprehensive resource for studying on pathogens of silkworm, including microsporidia, fungi, bacteria and virus. SilkPathDB provides access to not only genomic data including functional annotation of genes and gene products, but also extensive biological information for gene expression data and corresponding researches. SilkPathDB will be help with researches on pathogens of silkworm as well as other Lepidoptera insects.
NASA Life Sciences Portal is the next generation of the Life Sciences Data Archive for Human, Animal and Plant Research NASA's Human Research Program (HRP) conducts research and develops technologies that allow humans to travel safely and productively in space. The Program uses evidence from data collected on astronauts, as well as other supporting studies. These data are stored in the research data repository, Life Sciences Data Archive (LSDA).
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The Academic Data Repository of the National University of Rosario (RDA- UNR) allows for sharing, storing, accessing, exploring, and citing research data managed by UNR professors, researchers and students so as to make these data visible and promote its use and reutilization, ensuring its long-term preservation. It is a self-publishing repository, i.e. users upload, organize, describe and publish their own data with the assistance of a team of curators, user guides and training sessions.
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BCCM/ITM is a collection of well documented mycobacteria, characterized by phenotypic and/or genotypic tests. While having an emphasis on (drug-resistant) M. tuberculosis complex, BCCM/ITM comprises more than 90 mycobacterial species from human, animal and environmental origin from all continents.
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BCCM/IHEM is a fungal culture collection specialized in medical and veterinary mycology. About 16.000 strains of yeasts and moulds are available from all over the world: pathogens, allergenic species, strains producing mycotoxins, reference strains, teaching material, etc. It also comprises the Raymond Vanbreuseghem collection and the collection of Janssen Pharmaceutica. The BCCM/IHEM collection makes strains or their genomic DNA publicly available for medical, pharmaceutical and biological research, as well as for method validation, testing or educational purposes. Deposits of strains for public access are free of charge for the depositor. The collection also accept safe and patent deposits, and offers a range of services including trainings in mycology and identifications of strains. Moreover, BCCM/IHEM has expertise in fungal taxonomy, in MALDI-TOF MS identification of moulds and yeasts as well as in genomics (whole genome sequencing of fungal strains, phylogenomics, phylogenetics).
Academic Commons provides open, persistent access to the scholarship produced by researchers at Columbia University, Barnard College, Jewish Theological Seminary, Teachers College, and Union Theological Seminary. Academic Commons is a program of the Columbia University Libraries. Academic Commons accepts articles, dissertations, research data, presentations, working papers, videos, and more.
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bonndata is the institutional, FAIR-aligned and curated, cross-disciplinary research data repository for the publication of research data for all researchers at the University of Bonn. The repository is fully embedded into the University IT and Data Center and curated by the Research Data Service Center (https://www.forschungsdaten.uni-bonn.de/en). The software that bonndata is based on is the open source software Dataverse (https://dataverse.org)
The Research Collection is ETH Zurich's publication platform. It unites the functions of a university bibliography, an open access repository and a research data repository within one platform. Researchers who are affiliated with ETH Zurich, the Swiss Federal Institute of Technology, may deposit research data from all domains. They can publish data as a standalone publication, publish it as supplementary material for an article, dissertation or another text, share it with colleagues or a research group, or deposit it for archiving purposes. Research-data-specific features include flexible access rights settings, DOI registration and a DOI preview workflow, content previews for zip- and tar-containers, as well as download statistics and altmetrics for published data. All data uploaded to the Research Collection are also transferred to the ETH Data Archive, ETH Zurich’s long-term archive.
The PAIN Repository is a recently funded NIH initiative, which has two components: an archive for already collected imaging data (Archived Repository), and a repository for structural and functional brain images and metadata acquired prospectively using standardized acquisition parameters (Standardized Repository) in healthy control subjects and patients with different types of chronic pain. The PAIN Repository provides the infrastructure for storage of standardized resting state functional, diffusion tensor imaging and structural brain imaging data and associated biological, physiological and behavioral metadata from multiple scanning sites, and provides tools to facilitate analysis of the resulting comprehensive data sets.
METLIN represents the largest MS/MS collection of data with the database generated at multiple collision energies and in positive and negative ionization modes. The data is generated on multiple instrument types including SCIEX, Agilent, Bruker and Waters QTOF mass spectrometers.
The figshare service for the University of Sheffield allows researchers to store, share and publish research data. It helps the research data to be accessible by storing Metadata alongside datasets. Additionally, every uploaded item receives a Digital Object identifier (DOI), which allows the data to be citable and sustainable. If there are any ethical or copyright concerns about publishing a certain dataset, it is possible to publish the metadata associated with the dataset to help discoverability while sharing the data itself via a private channel through manual approval.
The Brain Biodiversity Bank refers to the repository of images of and information about brain specimens contained in the collections associated with the National Museum of Health and Medicine at the Armed Forces Institute of Pathology in Washington, DC. These collections include, besides the Michigan State University Collection, the Welker Collection from the University of Wisconsin, the Yakovlev-Haleem Collection from Harvard University, the Meyer Collection from the Johns Hopkins University, and the Huber-Crosby and Crosby-Lauer Collections from the University of Michigan and the C.U. Ariëns Kappers brain collection from Amsterdam Netherlands.Introducing online atlases of the brains of humans, sheep, dolphins, and other animals. A world resource for illustrations of whole brains and stained sections from a great variety of mammals
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.
The CancerData site is an effort of the Medical Informatics and Knowledge Engineering team (MIKE for short) of Maastro Clinic, Maastricht, The Netherlands. Our activities in the field of medical image analysis and data modelling are visible in a number of projects we are running. CancerData is offering several datasets. They are grouped in collections and can be public or private. You can search for public datasets in the NBIA (National Biomedical Imaging Archive) image archives without logging in.
EMPIAR, the Electron Microscopy Public Image Archive, is a public resource for raw, 2D electron microscopy images. Here, you can browse, upload, download and reprocess the thousands of raw, 2D images used to build a 3D structure. The purpose of EMPIAR is to provide an easy access to the state-of-the-art raw data to facilitate methods development and validation, which will lead to better 3D structures. It complements the Electron Microscopy Data Bank (EMDB), where 3D images are stored, and uses the fault-tolerant Aspera platform for data transfers
All ADNI data are shared without embargo through the LONI Image and Data Archive (IDA), a secure research data repository. Interested scientists may obtain access to ADNI imaging, clinical, genomic, and biomarker data for the purposes of scientific investigation, teaching, or planning clinical research studies. "The Alzheimer’s Disease Neuroimaging Initiative (ADNI) unites researchers with study data as they work to define the progression of Alzheimer’s disease (AD). ADNI researchers collect, validate and utilize data, including MRI and PET images, genetics, cognitive tests, CSF and blood biomarkers as predictors of the disease. Study resources and data from the North American ADNI study are available through this website, including Alzheimer’s disease patients, mild cognitive impairment subjects, and elderly controls. "
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DataverseNO (https://dataverse.no) is a curated, FAIR-aligned national generic repository for open research data from all academic disciplines. DataverseNO commits to facilitate that published data remain accessible and (re)usable in a long-term perspective. The repository is owned and operated by UiT The Arctic University of Norway. DataverseNO accepts submissions from researchers primarily from Norwegian research institutions. Datasets in DataverseNO are grouped into institutional collections as well as special collections. The technical infrastructure of the repository is based on the open source application Dataverse (https://dataverse.org), which is developed by an international developer and user community led by Harvard University.
Greengenes is an Earth Sciences website that assists clinical and environmental microbiologists from around the globe in classifying microorganisms from their local environments. A 16S rRNA gene database addresses limitations of public repositories by providing chimera screening, standard alignment, and taxonomic classification using multiple published taxonomies.
AceView provides a curated, comprehensive and non-redundant sequence representation of all public mRNA sequences (mRNAs from GenBank or RefSeq, and single pass cDNA sequences from dbEST and Trace). These experimental cDNA sequences are first co-aligned on the genome then clustered into a minimal number of alternative transcript variants and grouped into genes. Using exhaustively and with high quality standards the available cDNA sequences evidences the beauty and complexity of mammals’ transcriptome, and the relative simplicity of the nematode and plant transcriptomes. Genes are classified according to their inferred coding potential; many presumably non-coding genes are discovered. Genes are named by Entrez Gene names when available, else by AceView gene names, stable from release to release. Alternative features (promoters, introns and exons, polyadenylation signals) and coding potential, including motifs, domains, and homologies are annotated in depth; tissues where expression has been observed are listed in order of representation; diseases, phenotypes, pathways, functions, localization or interactions are annotated by mining selected sources, in particular PubMed, GAD and Entrez Gene, and also by performing manual annotation, especially in the worm. In this way, both the anatomy and physiology of the experimentally cDNA supported human, mouse and nematode genes are thoroughly annotated.
The DIP database catalogs experimentally determined interactions between proteins. It combines information from a variety of sources to create a single, consistent set of protein-protein interactions. The data stored within the DIP database were curated, both, manually by expert curators and also automatically using computational approaches that utilize the the knowledge about the protein-protein interaction networks extracted from the most reliable, core subset of the DIP data. Please, check the reference page to find articles describing the DIP database in greater detail. The Database of Ligand-Receptor Partners (DLRP) is a subset of DIP (Database of Interacting Proteins). The DLRP is a database of protein ligand and protein receptor pairs that are known to interact with each other. By interact we mean that the ligand and receptor are members of a ligand-receptor complex and, unless otherwise noted, transduce a signal. In some instances the ligand and/or receptor may form a heterocomplex with other ligands/receptors in order to be functional. We have entered the majority of interactions in DLRP as full DIP entries, with links to references and additional information