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Found 28 result(s)
The Federal Interagency Traumatic Brain Injury Research (FITBIR) informatics system was developed to share data across the entire TBI research field and to facilitate collaboration between laboratories, as well as interconnectivity with other informatics platforms. Sharing data, methodologies, and associated tools, rather than summaries or interpretations of this information, can accelerate research progress by allowing re-analysis of data, as well as re-aggregation, integration, and rigorous comparison with other data, tools, and methods. This community-wide sharing requires common data definitions and standards, as well as comprehensive and coherent informatics approaches.
A community platform to Share Data, Publish Data with a DOI, and get Citations. Advancing Spinal Cord Injury research through sharing of data from basic and clinical research.
OrthoMCL is a genome-scale algorithm for grouping orthologous protein sequences. It provides not only groups shared by two or more species/genomes, but also groups representing species-specific gene expansion families. So it serves as an important utility for automated eukaryotic genome annotation. OrthoMCL starts with reciprocal best hits within each genome as potential in-paralog/recent paralog pairs and reciprocal best hits across any two genomes as potential ortholog pairs. Related proteins are interlinked in a similarity graph. Then MCL (Markov Clustering algorithm,Van Dongen 2000; www.micans.org/mcl) is invoked to split mega-clusters. This process is analogous to the manual review in COG construction. MCL clustering is based on weights between each pair of proteins, so to correct for differences in evolutionary distance the weights are normalized before running MCL.
AmoebaDB belongs to the EuPathDB family of databases and is an integrated genomic and functional genomic database for Entamoeba and Acanthamoeba parasites. In its first iteration (released in early 2010), AmoebaDB contains the genomes of three Entamoeba species (see below). AmoebaDB integrates whole genome sequence and annotation and will rapidly expand to include experimental data and environmental isolate sequences provided by community researchers . The database includes supplemental bioinformatics analyses and a web interface for data-mining.
ToxoDB is a genome database for the genus Toxoplasma, a set of single-celled eukaryotic pathogens that cause human and animal diseases, including toxoplasmosis.
FungiDB belongs to the EuPathDB family of databases and is an integrated genomic and functional genomic database for the kingdom Fungi. FungiDB was first released in early 2011 as a collaborative project between EuPathDB and the group of Jason Stajich (University of California, Riverside). At the end of 2015, FungiDB was integrated into the EuPathDB bioinformatic resource center. FungiDB integrates whole genome sequence and annotation and also includes experimental and environmental isolate sequence data. The database includes comparative genomics, analysis of gene expression, and supplemental bioinformatics analyses and a web interface for data-mining.
The Mouse Tumor Biology (MTB) Database supports the use of the mouse as a model system of hereditary cancer by providing electronic access to: Information on endogenous spontaneous and induced tumors in mice, including tumor frequency & latency data, Information on genetically defined mice (inbred, hybrid, mutant, and genetically engineered strains of mice) in which tumors arise, Information on genetic factors associated with tumor susceptibility in mice and somatic genetic-mutations observed in the tumors, Tumor pathology reports and images, References, supporting MTB data and Links to other online resources for cancer.
Country
OCTOPUS is an Open Geospatial Consortium (OGC) compliant web-enabled database that allows users to visualise, query, and download cosmogenic 10Be and 26Al, luminescence, and radiocarbon ages and denudation rates associated with erosional landscapes, Quaternary depositional landforms and archaeological records, along with associated geospatial (vector and raster) data layers.
Country
The German Central Health Study Hub is a platform that serves two different kinds of users. First, it allows scientists and data holding organizations (data producers) to publish their project characteristics, documents and data related to their research endeavour in a FAIR manner. Obviously, patient-level data cannot be shared publicly, however, metadata describing the patient-level data along with information about data access can be shared via the platform (preservation description information). The other kind of user is a scientist or researcher (data consumer) that likes to find information about past and ongoing studies and is interested in reusing existing patient-level data for their project. To summarize, the platforms connect data providers with data consumers in the domain of clinical, public health and epidemiologic health research to foster reuse. The platform aggregates and harmonizes information already entered in various public repositories such as DRKS, clinicaltrials.gov, WHO ICTRP to provide a holistic view of the German research landscape in the aforementioned research areas. In addition, data stewards actively collect available information from (public) resources such as websites that cannot be automatically integrated. The service started during the COVID-19 pandemic.
Giardia lamblia is a significant, environmentally transmitted, human pathogen and an amitochondriate protist. It is a major contributor to the enormous worldwide burden of human diarrheal diseases, yet the basic biology of this parasite is not well understood. No virulence factor has been identified. The Giardia lamblia genome contains only 12 million base pairs distributed onto five chromosomes. Its analysis promises to provide insights about the origins of nuclear genome organization, the metabolic pathways used by parasitic protists, and the cellular biology of host interaction and avoidance of host immune systems. Since the divergence of Giardia lamblia lies close to the transition between eukaryotes and prokaryotes in universal ribosomal RNA phylogenies, it is a valuable, if not unique, model for gaining basic insights into genetic innovations that led to formation of eukaryotic cells. In evolutionary terms, the divergence of this organism is at least twice as ancient as the common ancestor for yeast and man. A detailed study of its genome will provide insights into an early evolutionary stage of eukaryotic chromosome organization as well as other aspects of the prokaryotic / eukaryotic divergence.
The Maize Genetics and Genomics Database focuses on collecting data related to the crop plant and model organism Zea mays. The project's goals are to synthesize, display, and provide access to maize genomics and genetics data, prioritizing mutant and phenotype data and tools, structural and genetic map sets, and gene models. MaizeGDB also aims to make the Maize Newsletter available, and provide support services to the community of maize researchers. MaizeGDB is working with the Schnable lab, the Panzea project, The Genome Reference Consortium, and iPlant Collaborative to create a plan for archiving, dessiminating, visualizing, and analyzing diversity data. MMaizeGDB is short for Maize Genetics/Genomics Database. It is a USDA/ARS funded project to integrate the data found in MaizeDB and ZmDB into a single schema, develop an effective interface to access this data, and develop additional tools to make data analysis easier. Our goal in the long term is a true next-generation online maize database.aize genetics and genomics database.
GigaDB primarily serves as a repository to host data and tools associated with articles published by GigaScience Press; GigaScience and GigaByte (both are online, open-access journals). GigaDB defines a dataset as a group of files (e.g., sequencing data, analyses, imaging files, software programs) that are related to and support a unit-of-work (article or study). GigaDB allows the integration of manuscript publication with supporting data and tools.
TCIA is a service which de-identifies and hosts a large archive of medical images of cancer accessible for public download. The data are organized as “collections”; typically patients’ imaging related by a common disease (e.g. lung cancer), image modality or type (MRI, CT, digital histopathology, etc) or research focus. Supporting data related to the images such as patient outcomes, treatment details, genomics and expert analyses are also provided when available.
Accredited through the MEDIN partnership, and core-funded by the Department for the Environment, Food and Rural Affairs (Defra) and the Scottish Government, DASSH provides tools and services for the long-term curation, management and publication of marine species and habitats data, within the UK and internationally. Working closely with partners and data providers we are committed to the FAIR Data Principles, to make marine biodiversity data Findable, Accessible, Interoperable and Reusable. DASSH is a flagship initiative of the Marine Biological Association (MBA), and builds on the MBA's historic role in marine science. Through partnerships with other UK and European data centres DASSH contributes to data portals including the NBN Atlas, EMODnet, EurOBIS and GBIF. On an international scale DASSH is also the UK node of the Ocean Biogeographic Information System (OBIS), and an Associated Data Unit of the International Oceanographic Data and Information Exchange (IODE), giving the Data Archive Centre global recognition.
EuPathDB (formerly ApiDB) is an integrated database covering the eukaryotic pathogens in the genera Acanthamoeba, Annacaliia, Babesia, Crithidia, Cryptosporidium, Edhazardia, Eimeria, Encephalitozoon, Endotrypanum, Entamoeba, Enterocytozoon, Giardia, Gregarina, Hamiltosporidium, Leishmania, Nematocida, Neospora, Nosema, Plasmodium, Theileria, Toxoplasma, Trichomonas, Trypanosoma and Vavraia, Vittaforma). While each of these groups is supported by a taxon-specific database built upon the same infrastructure, the EuPathDB portal offers an entry point to all of these resources, and the opportunity to leverage orthology for searches across genera.
Country
TERN's AEKOS data portal is the original gateway to Australian ecology data. It is a ‘data and research methods’ data portal for Australia’s land-dwelling plants, animals and their environments. The primary focus of data content is raw co-located ‘species and environment’ ecological survey data that has been collected at the ‘plot’ level to describe biodiversity, its patterns and ecological processes. It is openly accessible with standard discovery metadata and user-oriented, contextual metadata critical for data reuse. Our services support the ecosystem science community, land managers and governments seeking to publish under COPE publishing ethics and the FAIR data publishing principles. AEKOS is registered with Thomson & Reuters Data Citation Index and is a recommended repository of Nature Publishing’s Scientific Data. There are currently 97,037 sites covering mostly plant biodiversity and co-located environmental data of Australia. The AEKOS initiative is supported by TERN (tern.org.au), hosted by The University of Adelaide and funded by the Australian Government’s National Research Infrastructure for Australia.
B2SAFE is a robust, safe and highly available service which allows community and departmental repositories to implement data management policies on their research data across multiple administrative domains in a trustworthy manner. A solution to: provide an abstraction layer which virtualizes large-scale data resources, guard against data loss in long-term archiving and preservation, optimize access for users from different regions, bring data closer to powerful computers for compute-intensive analysis
This data repository contains the experimental data produced at the ISIS Neutron and Muon Source (https://www.isis.stfc.ac.uk/Pages/home.aspx/) in the UK Science and Technology Facilities Council (STFC, https://www.ukri.org/councils/stfc/). The repository contains the open data as well as the data under embargoed that can be accessed by the data producers.
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NCI Imaging Data Commons (IDC) is a cloud-based repository of publicly available cancer imaging data co-located with the analysis and exploration tools and resources. IDC is a node within the broader NCI Cancer Research Data Commons (CRDC) infrastructure that provides secure access to a large, comprehensive, and expanding collection of cancer research data.