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Found 13 result(s)
MGI is the international database resource for the laboratory mouse, providing integrated genetic, genomic, and biological data to facilitate the study of human health and disease. The projects contributing to this resource are: Mouse Genome Database (MGD) Project, Gene Expression Database (GXD) Project, Mouse Tumor Biology (MTB) Database Project, Gene Ontology (GO) Project at MGI, MouseMine Project, MouseCyc Project at MGI
Reactome is a manually curated, peer-reviewed pathway database, annotated by expert biologists and cross-referenced to bioinformatics databases. Its aim is to share information in the visual representations of biological pathways in a computationally accessible format. Pathway annotations are authored by expert biologists, in collaboration with Reactome editorial staff and cross-referenced to many bioinformatics databases. These include NCBI Gene, Ensembl and UniProt databases, the UCSC and HapMap Genome Browsers, the KEGG Compound and ChEBI small molecule databases, PubMed, and Gene Ontology.
ModelDB is a curated database of published models in the broad domain of computational neuroscience. It addresses the need for access to such models in order to evaluate their validity and extend their use. It can handle computational models expressed in any textual form, including procedural or declarative languages (e.g. C++, XML dialects) and source code written for any simulation environment. The model source code doesn't even have to reside inside ModelDB; it just has to be available from some publicly accessible online repository or WWW site.
The German Neuroinformatics Node's data infrastructure (GIN) services provide a platform for comprehensive and reproducible management and sharing of neuroscience data. Building on well established versioning technology, GIN offers the power of a web based repository management service combined with a distributed file storage. The service addresses the range of research data workflows starting from data analysis on the local workstation to remote collaboration and data publication.
This project is an open invitation to anyone and everyone to participate in a decentralized effort to explore the opportunities of open science in neuroimaging. We aim to document how much (scientific) value can be generated from a data release — from the publication of scientific findings derived from this dataset, algorithms and methods evaluated on this dataset, and/or extensions of this dataset by acquisition and incorporation of new data. The project involves the processing of acoustic stimuli. In this study, the scientists have demonstrated an audiodescription of classic "Forrest Gump" to subjects, while researchers using functional magnetic resonance imaging (fMRI) have captured the brain activity of test candidates in the processing of language, music, emotions, memories and pictorial representations.In collaboration with various labs in Magdeburg we acquired and published what is probably the most comprehensive sample of brain activation patterns of natural language processing. Volunteers listened to a two-hour audio movie version of the Hollywood feature film "Forrest Gump" in a 7T MRI scanner. High-resolution brain activation patterns and physiological measurements were recorded continuously. These data have been placed into the public domain, and are freely available to the scientific community and the general public.
<<!! checked 20.03.2017 SumsDB was offline; for more information see!! >> SumsDB (the Surface Management System DataBase) is a repository of brain-mapping data (surfaces & volumes; structural & functional data) from many laboratories.
Neuroimaging Tools and Resources Collaboratory (NITRC) is currently a free one-stop-shop environment for science researchers that need resources such as neuroimaging analysis software, publicly available data sets, and computing power. Since its debut in 2007, NITRC has helped the neuroscience community to use software and data produced from research that, before NITRC, was routinely lost or disregarded, to make further discoveries. NITRC provides free access to data and enables pay-per-use cloud-based access to unlimited computing power, enabling worldwide scientific collaboration with minimal startup and cost. With NITRC and its components—the Resources Registry (NITRC-R), Image Repository (NITRC-IR), and Computational Environment (NITRC-CE)—a researcher can obtain pilot or proof-of-concept data to validate a hypothesis for a few dollars.
PhysioNet is an on-line forum for the dissemination and exchange of recorded biomedical signals and open-source software for analyzing them. It provides facilities for the cooperative analysis of data and the evaluation of proposed new algorithms. In addition to providing free electronic access to PhysioBank data and PhysioToolkit software via the World Wide Web. PhysioNet offers services and training via on-line tutorials to assist users with varying levels of expertise. PhysioNet is a resource for biomedical research and development. It has three closely interdependent components: PhysioBank is a large and growing archive of well-characterized digital recordings of physiologic signals, time series, and related data for use by the biomedical research community. PhysioBank currently includes more than 60 collections of cardiopulmonary, neural, and other biomedical signals from healthy subjects and patients with a variety of conditions with major public health implications, including sudden cardiac death, congestive heart failure, epilepsy, gait disorders, sleep apnea, and aging. PhysioToolkit is a large and growing library of software for physiologic signal processing and analysis, detection of physiologically significant events using both classical techniques and novel methods based on statistical physics and nonlinear dynamics, interactive display and characterization of signals, creation of new databases, simulation of physiologic and other signals, quantitative evaluation and comparison of analysis methods, and analysis of nonequilibrium and nonstationary processes. PhysioNetWorks is a virtual laboratory where you can work together with us and with colleagues anywhere in the world to create, evaluate, improve, document, and prepare new data and software "works" for publication on PhysioNet. Unlike all other parts of the PhysioNet web site, access to PhysioNetWorks is password-protected. (Accounts are free and a password can be obtained in a minute or two.)
INDI was formed as a next generation FCP effort. INDI aims to provide a model for the broader imaging community while simultaneously creating a public dataset capable of dwarfing those that most groups could obtain individually.
The National Database for Autism Research (NDAR) is an NIH-funded research data repository that aims to accelerate progress in autism spectrum disorders (ASD) research through data sharing, data harmonization, and the reporting of research results. NDAR also serves as a scientific community platform and portal to multiple other research repositories, allowing for aggregation and secondary analysis of data. NDAR combines the function of a data repository, which holds genetic, phenotypic, clinical, and medical imaging data, and the function of a scientific community platform, which defines the standard tools and policies to integrate the computational resources developed by scientific research institutions, private foundations, and other federal and state agencies supporting ASD research. Furthermore, NDAR is working to develop the means to connect relevant repositories together through data federation.
The OpenfMRI project was established in 2010 to provide a resource for researchers interested in making their fMRI data openly available to the research community. It is managed by Russ Poldrack at the University of Texas at Austin, with computing resources provided by the Texas Advanced Computing Center. The OpenfMRI project is funded by a grant from the National Science Foundation.
database of pSILAC data – information about changes in mRNA levels and protein synthesis following microRNA misexpression in HeLa cells