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caNanoLab is a data sharing portal designed to facilitate information sharing in the biomedical nanotechnology research community to expedite and validate the use of nanotechnology in biomedicine. caNanoLab provides support for the annotation of nanomaterials with characterizations resulting from physico-chemical and in vitro assays and the sharing of these characterizations and associated nanotechnology protocols in a secure fashion.
>>>!!!<<< The repository is no longer available. >>>!!!<<< The eagle-i National Network and eagle-i resource search at www.eagle-.net was retired on November 4, 2021.!!! Groundbreaking biomedical research requires access to cutting edge scientific resources; however such resources are often invisible beyond the laboratories or universities where they were developed. eagle-i is a discovery platform that helps biomedical scientists find previously invisible, but highly valuable, resources.
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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The RAMEDIS system is a platform independent, web-based information system for rare metabolic diseases based on filed case reports. It was developed in close cooperation with clinical partners to allow them to collect information on rare metabolic diseases with extensive details, e.g. about occurring symptoms, laboratory findings, therapy and molecular data.
This Animal Quantitative Trait Loci (QTL) database (Animal QTLdb) is designed to house all publicly available QTL and trait mapping data (i.e. trait and genome location association data; collectively called "QTL data" on this site) on livestock animal species for easily locating and making comparisons within and between species. New database tools are continuely added to align the QTL and association data to other types of genome information, such as annotated genes, RH / SNP markers, and human genome maps. Besides the QTL data from species listed below, the QTLdb is open to house QTL/association date from other animal species where feasible. Note that the JAS along with other journals, now require that new QTL/association data be entered into a QTL database as part of their publication requirements.
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 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.
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MyTardis began at Monash University to solve the problem of users needing to store large datasets and share them with collaborators online. Its particular focus is on integration with scientific instruments, instrument facilities and research lab file storage. Our belief is that the less effort a researcher has to expend safely storing data, the more likely they are to do so. This approach has flourished with MyTardis capturing data from areas such as protein crystallography, electron microscopy, medical imaging and proteomics and with deployments at Australian institutions such as University of Queensland, RMIT, University of Sydney and the Australian Synchrotron. Data access via https://www.massive.org.au/ and https://store.erc.monash.edu.au/experiment/view/104/ and see 'remarks'.
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 Copernicus Marine Environment Monitoring Service (CMEMS) provides regular and systematic reference information on the physical and biogeochemical state, variability and dynamics of the ocean and marine ecosystems for the global ocean and the European regional seas. The observations and forecasts produced by the service support all marine applications, including: Marine safety; Marine resources; Coastal and marine environment; Weather, seasonal forecasting and climate. For instance, the provision of data on currents, winds and sea ice help to improve ship routing services, offshore operations or search and rescue operations, thus contributing to marine safety. The service also contributes to the protection and the sustainable management of living marine resources in particular for aquaculture, sustainable fisheries management or regional fishery organisations decision-making process. Physical and marine biogeochemical components are useful for water quality monitoring and pollution control. Sea level rise is a key indicator of climate change and helps to assess coastal erosion. Sea surface temperature elevation has direct consequences on marine ecosystems and appearance of tropical cyclones. As a result of this, the service supports a wide range of coastal and marine environment applications. Many of the data delivered by the service (e.g. temperature, salinity, sea level, currents, wind and sea ice) also play a crucial role in the domain of weather, climate and seasonal forecasting.
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).
VertNet is a NSF-funded collaborative project that makes biodiversity data free and available on the web. VertNet is a tool designed to help people discover, capture, and publish biodiversity data. It is also the core of a collaboration between hundreds of biocollections that contribute biodiversity data and work together to improve it. VertNet is an engine for training current and future professionals to use and build upon best practices in data quality, curation, research, and data publishing. Yet, VertNet is still the aggregate of all of the information that it mobilizes. To us, VertNet is all of these things and more.
Gemma is a database for the meta-analysis, re-use and sharing of genomics data, currently primarily targeted at the analysis of gene expression profiles. Gemma contains data from thousands of public studies, referencing thousands of published papers. Users can search, access and visualize co-expression and differential expression results.
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.
Brainlife promotes engagement and education in reproducible neuroscience. We do this by providing an online platform where users can publish code (Apps), Data, and make it "alive" by integragrate various HPC and cloud computing resources to run those Apps. Brainlife also provide mechanisms to publish all research assets associated with a scientific project (data and analyses) embedded in a cloud computing environment and referenced by a single digital-object-identifier (DOI). The platform is unique because of its focus on supporting scientific reproducibility beyond open code and open data, by providing fundamental smart mechanisms for what we refer to as “Open Services.”
Project Achilles is a systematic effort aimed at identifying and cataloging genetic vulnerabilities across hundreds of genomically characterized cancer cell lines. The project uses genome-wide genetic perturbation reagents (shRNAs or Cas9/sgRNAs) to silence or knock-out individual genes and identify those genes that affect cell survival. Large-scale functional screening of cancer cell lines provides a complementary approach to those studies that aim to characterize the molecular alterations (e.g. mutations, copy number alterations) of primary tumors, such as The Cancer Genome Atlas (TCGA). The overall goal of the project is to identify cancer genetic dependencies and link them to molecular characteristics in order to prioritize targets for therapeutic development and identify the patient population that might benefit from such targets. Project Achilles data is hosted on the Cancer Dependency Map Portal (DepMap) where it has been harmonized with our genomics and cellular models data. You can access the latest and all past datasets here: https://depmap.org/portal/download/all/
OpenWorm aims to build the first comprehensive computational model of the Caenorhabditis elegans (C. elegans), a microscopic roundworm. With only a thousand cells, it solves basic problems such as feeding, mate-finding and predator avoidance. Despite being extremely well studied in biology, this organism still eludes a deep, principled understanding of its biology. We are using a bottom-up approach, aimed at observing the worm behaviour emerge from a simulation of data derived from scientific experiments carried out over the past decade. To do so we are incorporating the data available in the scientific community into software models. We are engineering Geppetto and Sibernetic, open-source simulation platforms, to be able to run these different models in concert. We are also forging new collaborations with universities and research institutes to collect data that fill in the gaps All the code we produce in the OpenWorm project is Open Source and available on GitHub.
NKN is now Research Computing and Data Services (RCDS)! We provide data management support for UI researchers and their regional, national, and international collaborators. This support keeps researchers at the cutting-edge of science and increases our institution's competitiveness for external research grants. Quality data and metadata developed in research projects and curated by RCDS (formerly NKN) is a valuable, long-term asset upon which to develop and build new research and science.
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GnpIS is a multispecies integrative information system dedicated to plant and fungi pests. It bridges genetic and genomic data, allowing researchers access to both genetic information (e.g. genetic maps, quantitative trait loci, association genetics, markers, polymorphisms, germplasms, phenotypes and genotypes) and genomic data (e.g. genomic sequences, physical maps, genome annotation and expression data) for species of agronomical interest. GnpIS is used by both large international projects and plant science departments at the French National Research Institute for Agriculture, Food and Environment. It is regularly improved and released several times per year. GnpIS is accessible through a web portal and allows to browse different types of data either independently through dedicated interfaces or simultaneously using a quick search ('google like search') or advanced search (Biomart, Galaxy, Intermine) tools.
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Sextant is a marine and coastal geographic data infrastructure. It is operated by Scientific Information Systems for the Sea (SISMER) of Ifremer (https://www.ifremer.fr/). Sextant aims to document, disseminate and promote a catalog of data related to the marine environment. For Ifremer's laboratories and partners, as well as for national and European actors working in the marine and coastal field, Sextant provides tools that promote and facilitate the archiving, consultation and availability of these geographical data. Data published by Sextant are available free or restricted. They can be used in accordance with the terms of the Creative Commons license selected by the author of data. Sextant infrastructure and the technologies used are in line with the implementation of the INSPIRE Directive and make it possible to follow the Open Data approach. Some data set published by Sextant has a DOI which enables it to be cited in a publication in a reliable and sustainable way. The long-term preservation of data filed in Sextant is ensured by Ifremer infrastructure.
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
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National ecosystem data bank (EcoDB) is a public professional scientific data repository supported by the National Ecosystem Science Data Center (NESDC) for researchers in ecology and related fields, which provides long-term preservation, publication, sharing and access services of scientific data. EcoDB provides services for both individual researchers and scientific journals. Individuals can use this repository to store, manage and publish scientific data, get feedback from others on the data, and discover scientific data shared by others through this repository. Journals can use the repository to gather, manage and review the supporting data of submitted paper. At the same time, journals can timely publish these supporting data according to their own data policies.
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.