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Found 29 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.
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BExIS is the online data repository and information system of the Biodiversity Exploratories Project (BE). The BE is a German network of biodiversity related working groups from areas such as vegetation and soil science, zoology and forestry. Up to three years after data acquisition, the data use is restricted to members of the BE. Thereafter, the data is usually public available (https://www.bexis.uni-jena.de/ddm/publicsearch/index).
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.
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
The MG-RAST server is an open source system for annotation and comparative analysis of metagenomes. Users can upload raw sequence data in fasta format; the sequences will be normalized and processed and summaries automatically generated. The server provides several methods to access the different data types, including phylogenetic and metabolic reconstructions, and the ability to compare the metabolism and annotations of one or more metagenomes and genomes. In addition, the server offers a comprehensive search capability. Access to the data is password protected, and all data generated by the automated pipeline is available for download in a variety of common formats. MG-RAST has become an unofficial repository for metagenomic data, providing a means to make your data public so that it is available for download and viewing of the analysis without registration, as well as a static link that you can use in publications. It also requires that you include experimental metadata about your sample when it is made public to increase the usefulness to the community.
Xenbase's mission is to provide the international research community with a comprehensive, integrated and easy to use web based resource that gives access the diverse and rich genomic, expression and functional data available from Xenopus research. Xenbase also provides a critical data sharing infrastructure for many other NIH-funded projects, and is a focal point for the Xenopus community. In addition to our primary goal of supporting Xenopus researchers, Xenbase enhances the availability and visibility of Xenopus data to the broader biomedical research community.
ICRISAT performs crop improvement research, using conventional as well as methods derived from biotechnology, on the following crops: Chickpea, Pigeonpea, Groundnut, Pearl millet,Sorghum and Small millets. ICRISAT's data repository collects, preserves and facilitates access to the datasets produced by ICRISAT researchers to all users who are interested in. Data includes Phenotypic, Genotypic, Social Science, and Spatial data, Soil and Weather.
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'Redape' is a digital repository that aims to preserve and disseminate research data produced by the Brazilian Agricultural Research Corporation - Embrapa. It allows the organization, management and publication of data in accordance with the FAIR principles.
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
ETH Data Archive is ETH Zurich's long-term preservation solution for digital information such as research data, digitised content, archival records, or images. It serves as the backbone of data curation and for most of its content, it is a “dark archive” without public access. In this capacity, the ETH Data Archive also archives the content of ETH Zurich’s Research Collection which is the primary repository for members of the university and the first point of contact for publication of data at ETH Zurich. All data that was produced in the context of research at the ETH Zurich, can be published and archived in the Research Collection. An automated connection to the ETH Data Archive in the background ensures the medium to long-term preservation of all publications and research data. Direct access to the ETH Data Archive is intended only for customers who need to deposit software source code within the framework of ETH transfer Software Registration. Open Source code packages and other content from legacy workflows can be accessed via ETH Library @ swisscovery (https://library.ethz.ch/en/).
The KNB Data Repository is an international repository intended to facilitate ecological, environmental and earth science research in the broadest senses. For scientists, the KNB Data Repository is an efficient way to share, discover, access and interpret complex ecological, environmental, earth science, and sociological data and the software used to create and manage those data. Due to rich contextual information provided with data in the KNB, scientists are able to integrate and analyze data with less effort. The data originate from a highly-distributed set of field stations, laboratories, research sites, and individual researchers. The KNB supports rich, detailed metadata to promote data discovery as well as automated and manual integration of data into new projects. The KNB supports a rich set of modern repository services, including the ability to assign Digital Object Identifiers (DOIs) so data sets can be confidently referenced in any publication, the ability to track the versions of datasets as they evolve through time, and metadata to establish the provenance relationships between source and derived data.
DataON is Korea's National Research Data Platform. It provides integrated search of metadata for KISTI's research data and domestic and international research data and links to raw data. DataON allows users (researchers, policy makers, etc.) to perform the following tasks: Easily search for various types of research data in all scientific fields. By registering research results, research data can be posted and cited. Build a community among researchers and enable collaborative research. It provides a data analysis environment that allows one-stop analysis of discovered research data.
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In the framework of the Collaborative Research Centre/Transregio 32 ‘Patterns in Soil-Vegetation-Atmosphere Systems: Monitoring, Modelling, and Data Assimilation’ (CRC/TR32, www.tr32.de), funded by the German Research Foundation from 2007 to 2018, a RDM system was self-designed and implemented. The so-called CRC/TR32 project database (TR32DB, www.tr32db.de) is operating online since early 2008. The TR32DB handles all data including metadata, which are created by the involved project participants from several institutions (e.g. Universities of Cologne, Bonn, Aachen, and the Research Centre Jülich) and research fields (e.g. soil and plant sciences, hydrology, geography, geophysics, meteorology, remote sensing). The data is resulting from several field measurement campaigns, meteorological monitoring, remote sensing, laboratory studies and modelling approaches. Furthermore, outcomes of the scientists such as publications, conference contributions, PhD reports and corresponding images are collected in the TR32DB.
GenBank® is a comprehensive database that contains publicly available nucleotide sequences for almost 260 000 formally described species. These sequences are obtained primarily through submissions from individual laboratories and batch submissions from large-scale sequencing projects, including whole-genome shotgun (WGS) and environmental sampling projects. Most submissions are made using the web-based BankIt or standalone Sequin programs, and GenBank staff assigns accession numbers upon data receipt. Daily data exchange with the European Nucleotide Archive (ENA) and the DNA Data Bank of Japan (DDBJ) ensures worldwide coverage. GenBank is accessible through the NCBI Entrez retrieval system, which integrates data from the major DNA and protein sequence databases along with taxonomy, genome, mapping, protein structure and domain information, and the biomedical journal literature via PubMed. BLAST provides sequence similarity searches of GenBank and other sequence databases. Complete bimonthly releases and daily updates of the GenBank database are available by FTP.
The Open Science Framework (OSF) is part network of research materials, part version control system, and part collaboration software. The purpose of the software is to support the scientist's workflow and help increase the alignment between scientific values and scientific practices. Document and archive studies. Move the organization and management of study materials from the desktop into the cloud. Labs can organize, share, and archive study materials among team members. Web-based project management reduces the likelihood of losing study materials due to computer malfunction, changing personnel, or just forgetting where you put the damn thing. Share and find materials. With a click, make study materials public so that other researchers can find, use and cite them. Find materials by other researchers to avoid reinventing something that already exists. Detail individual contribution. Assign citable, contributor credit to any research material - tools, analysis scripts, methods, measures, data. Increase transparency. Make as much of the scientific workflow public as desired - as it is developed or after publication of reports. Find public projects here. Registration. Registering materials can certify what was done in advance of data analysis, or confirm the exact state of the project at important points of the lifecycle such as manuscript submission or at the onset of data collection. Discover public registrations here. Manage scientific workflow. A structured, flexible system can provide efficiency gain to workflow and clarity to project objectives, as pictured.
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DAIS - Digital Archive of the Serbian Academy of Sciences and Arts is a joint digital repository of the Serbian Academy of Sciences and Arts (SASA) and the research institutes under the auspices of SASA. The aim of the repository is to provide open access to publications and other research outputs resulting from the projects implemented by the SASA and its institutes. The repository uses a DSpace-based software platform developed and maintained by the Belgrade University Computer Centre (RCUB).
The Database explores the interactions of chemicals and proteins. It integrates information about interactions from metabolic pathways, crystal structures, binding experiments and drug-target relationships. Inferred information from phenotypic effects, text mining and chemical structure similarity is used to predict relations between chemicals. STITCH further allows exploring the network of chemical relations, also in the context of associated binding proteins.
SimTK is a free project-hosting platform for the biomedical computation community that enables researchers to easily share their software, data, and models and provides the infrastructure so they can support and grow a community around their projects. It has over 126.656 members, hosts 1.648 projects from researchers around the world, and has had more than 2.095.783 files downloaded from it. Individuals have created SimTK projects to meet publisher and funding agencies’ software and data sharing requirements, run scientific challenges, create a collection of their community’s resources, and much more.
I2D (Interologous Interaction Database) is an on-line database of known and predicted mammalian and eukaryotic protein-protein interactions. It has been built by mapping high-throughput (HTP) data between species. Thus, until experimentally verified, these interactions should be considered "predictions". It remains one of the most comprehensive sources of known and predicted eukaryotic PPI. I2D includes data for S. cerevisiae, C. elegans, D. melonogaster, R. norvegicus, M. musculus, and H. sapiens.
The International Food Policy Research Institute (IFPRI) seeks sustainable solutions for ending hunger and poverty. In collaboration with institutions throughout the world, IFPRI is often involved in the collection of primary data and the compilation and processing of secondary data. The resulting datasets provide a wealth of information at the local (household and community), national, and global levels. IFPRI freely distributes as many of these datasets as possible and encourages their use in research and policy analysis. IFPRI Dataverse contains following dataverses: Agricultural Science and Knowledge Indicators - ASTI, HarvestChoice, Statistics on Public Expenditures for Economic Development - SPEED, International Model for Policy Analysis of Agricultural Commodities and Trade - IMPACT, Africa RISING Dataverse and Food Security Portal Dataverse.