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Found 9 result(s)

NeuroVault

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A place where researchers can publicly store and share unthresholded statistical maps, parcellations, and atlases produced by MRI and PET studies.

DANDI

Distributed Archives for Neurophysiology Data Integration

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The US BRAIN Initiative archive for publishing and sharing neurophysiology data including electrophysiology, optophysiology, and behavioral time-series, and images from immunostaining experiments.

DEIMS-SDR

Dynamic Ecological Information Management System - Site and Dataset Registry

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DEIMS-SDR (Dynamic Ecological Information Management System - Site and dataset registry) is an information management system that allows you to discover long-term ecosystem research sites around the globe, along with the data gathered at those sites and the people and networks associated with them. DEIMS-SDR describes a wide range of sites, providing a wealth of information, including each site’s location, ecosystems, facilities, parameters measured and research themes. It is also possible to access a growing number of datasets and data products associated with the sites. All sites and dataset records can be referenced using unique identifiers that are generated by DEIMS-SDR. It is possible to search for sites via keyword, predefined filters or a map search. By including accurate, up to date information in DEIMS, site managers benefit from greater visibility for their LTER site, LTSER platform and datasets, which can help attract funding to support site investments. The aim of DEIMS-SDR is to be the globally most comprehensive catalogue of environmental research and monitoring facilities, featuring foremost but not exclusively information about all LTER sites on the globe and providing that information to science, politics and the public in general.

COVID-19 Data Portal

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The COVID-19 Data Portal was launched in April 2020 to bring together relevant datasets for sharing and analysis in an effort to accelerate coronavirus research. It enables researchers to upload, access and analyse COVID-19 related reference data and specialist datasets as part of the wider European COVID-19 Data Platform.

Critical Zone Observatories data

CZO data

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The NSF-supported Program serves the international scientific community through research, infrastructure, data, and models. We focus on how components of the Critical Zone interact, shape Earth's surface, and support life. ARCHIVED CONTENT: In December 2020, the CZO program was succeeded by the Critical Zone Collaborative Network (CZ Net) https://criticalzone.org/

bio.tools

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bio.tools is a software registry for bioinformatics and the life sciences.

System for Earth Sample Registration

SESAR

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SESAR, the System for Earth Sample Registration, is a global registry for specimens (rocks, sediments, minerals, fossils, fluids, gas) and related sampling features from our natural environment. SESAR's objective is to overcome the problem of ambiguous sample naming in the Earth Sciences. SESAR maintains a database of sample records that are contributed by its users. Each sample that is registered with SESAR is assigned an International Geo Sample Number IGSN to ensure its global unique identification.

ROHub

Research Object Hub Platform

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ROHub is a holistic solution for the storage, lifecycle management and preservation of scientific investigations, campaigns and operational processes via research objects. It makes these resources available to others, allows to publish and release them through a DOI, and allows to discover and reuse pre-existing scientific knowledge. Built entirely around the research object concept and inspired by sustainable software management principles, ROHub is the reference platform implementing natively the full research object model and paradigm, which provides the backbone to a wealth of RO-centric applications and interfaces across different scientific communities.

PSnpBind

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PSnpBind is a large database of protein–ligand complexes covering a wide range of binding pocket mutations and small molecules’ landscape. This database can be used as a source of data for different types of studies, for example, developing machine learning algorithms to predict protein–ligand affinity or mutation's effect on it which requires an extensive amount of data with a wide coverage of mutation types and small molecules. Also, studies of protein-ligand interactions and conformer orientation changes across different mutated versions of a protein can be established using data from PSnpBind.