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Found 45 result(s)
>>>>!!!<<< As stated 2017-06-27 The website http://researchcompendia.org is no longer available; repository software is archived on github https://github.com/researchcompendia >>>!!!<<< The ResearchCompendia platform is an attempt to use the web to enhance the reproducibility and verifiability—and thus the reliability—of scientific research. we provide the tools to publish the "actual scholarship" by hosting data, code, and methods in a form that is accessible, trackable, and persistent. Some of our short term goals include: To expand and enhance the platform including adding executability for a greater variety of coding languages and frameworks, and enhancing output presentation. To expand usership and to test the ResearchCompendia model in a number of additional fields, including computational mathematics, statistics, and biostatistics. To pilot integration with existing scholarly platforms, enabling researchers to discover relevant Research Compendia websites when looking at online articles, code repositories, or data archives.
>>>!!!<<< SMD has been retired. After approximately fifteen years of microarray-centric research service, the Stanford Microarray Database has been retired. We apologize for any inconvenience; please read below for possible resolutions to your queries. If you are looking for any raw data that was directly linked to SMD from a manuscript, please search one of the public repositories. NCBI Gene Expression Omnibus EBI ArrayExpress All published data were previously communicated to one (or both) of the public repositories. Alternatively, data for publications between 1997 and 2004 were likely migrated to the Princeton University MicroArray Database, and are accessible there. If you are looking for a manuscript supplement (i.e. from a domain other than smd.stanford.edu), perhaps try searching the Internet Archive: Wayback Machine https://archive.org/web/ . >>>!!!<<< The Stanford Microarray Database (SMD) is a DNA microarray research database that provides a large amount of data for public use.
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 Digital Archaeological Record (tDAR) is an international digital repository for the digital records of archaeological investigations. tDAR’s use, development, and maintenance are governed by Digital Antiquity, an organization dedicated to ensuring the long-term preservation of irreplaceable archaeological data and to broadening the access to these data.
The Magnetics Information Consortium (MagIC) improves research capacity in the Earth and Ocean sciences by maintaining an open community digital data archive for rock magnetic, geomagnetic, archeomagnetic (archaeomagnetic) and paleomagnetic (palaeomagnetic) data. Different parts of the website allow users access to archive, search, visualize, and download these data. MagIC supports the international rock magnetism, geomagnetism, archeomagnetism (archaeomagnetism), and paleomagnetism (palaeomagnetism) research and endeavors to bring data out of private archives, making them accessible to all and (re-)useable for new, creative, collaborative scientific and educational activities. The data in MagIC is used for many types of studies including tectonic plate reconstructions, geomagnetic field models, paleomagnetic field reversal studies, magnetohydrodynamical studies of the Earth's core, magnetostratigraphy, and archeology. MagIC is a domain-specific data repository and directed by PIs who are both producers and consumers of rock, geo, and paleomagnetic data. Funded by NSF since 2003, MagIC forms a major part of https://earthref.org which integrates four independent cyber-initiatives rooted in various parts of the Earth, Ocean and Life sciences and education.
<<<!!!<<< The RDP website is no longer available. A stand-alone version of the RDP Classifier is available on Sorceforge https://sourceforge.net/projects/rdp-classifier/. Instructions for installing a command-line version of RDP Tools can be found at Dr. J.Quensen's Website https://john-quensen.com/tutorials/tutorial-1/ and https://jfq3.gitbook.io/rdptools-docker/rdptools-docker/readme. >>>!!!>>>
<<!! checked 20.03.2017 SumsDB was offline; for more information and archive see http://brainvis.wustl.edu/sumsdb/ >> SumsDB (the Surface Management System DataBase) is a repository of brain-mapping data (surfaces & volumes; structural & functional data) from many laboratories.
>>>>!!!<<<<As of March 28, 2016, the 'NSF Arctic Data Center' will serve as the current repository for NSF-funded Arctic data. The ACADIS Gateway http://www.aoncadis.org is no longer accepting data submissions. All data and metadata in the ACADIS system have been transferred to the NSF Arctic Data Center system. There is no need for you to resubmit existing data. >>>>!!!<<<< ACADIS is a repository for Arctic research data to provide data archival, preservation and access for all projects funded by NSF's Arctic Science Program (ARC). Data include long-term observational timeseries, local, regional, and system-scale research from many diverse domains. The Advanced Cooperative Arctic Data and Information Service (ACADIS) program includes data management services.
Human Proteinpedia is a community portal for sharing and integration of human protein data. This is a joint project between Pandey at Johns Hopkins University, and Institute of Bioinformatics, Bangalore. This portal allows research laboratories around the world to contribute and maintain protein annotations. Human Protein Reference Database (HPRD) integrates data, that is deposited in Human Proteinpedia along with the existing literature curated information in the context of an individual protein. All the public data contributed to Human Proteinpedia can be queried, viewed and downloaded. Data pertaining to post-translational modifications, protein interactions, tissue expression, expression in cell lines, subcellular localization and enzyme substrate relationships may be deposited.
The Health and Retirement Study (HRS) is a longitudinal panel study that surveys a representative sample of more than 26,000 Americans over the age of 50 every two years. The study has collected information about income, work, assets, pension plans, health insurance, disability, physical health and functioning, cognitive functioning, genetic information and health care expenditures.
A data repository and social network so that researchers can interact and collaborate, also offers tutorials and datasets for data science learning. "data.world is designed for data and the people who work with data. From professional projects to open data, data.world helps you host and share your data, collaborate with your team, and capture context and conclusions as you work."
A research data repository for the education and developmental sciences.
The Polinsky Language Sciences Lab at Harvard University is a linguistics lab that examines questions of language structure and its effect on the ways in which people use and process language in real time. We engage in linguistic and interdisciplinary research projects ourselves; offer linguistic research capabilities for undergraduate and graduate students, faculty, and visitors; and build relationships with the linguistic communities in which we do our research. We are interested in a broad range of issues pertaining to syntax, interfaces, and cross-linguistic variation. We place a particular emphasis on novel experimental evidence that facilitates the construction of linguistic theory. We have a strong cross-linguistic focus, drawing upon English, Russian, Chinese, Korean, Mayan languages, Basque, Austronesian languages, languages of the Caucasus, and others. We believe that challenging existing theories with data from as broad a range of languages as possible is a crucial component of the successful development of linguistic theory. We investigate both fluent speakers and heritage speakers—those who grew up hearing or speaking a particular language but who are now more fluent in a different, societally dominant language. Heritage languages, a novel field of linguistic inquiry, are important because they provide new insights into processes of linguistic development and attrition in general, thus increasing our understanding of the human capacity to maintain and acquire language. Understanding language use and processing in real time and how children acquire language helps us improve language study and pedagogy, which in turn improves communication across the globe. Although our lab does not specialize in language acquisition, we have conducted some studies of acquisition of lesser-studied languages and heritage languages, with the purpose of comparing heritage speakers to adults.
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.
ScienceBase provides access to aggregated information derived from many data and information domains, including feeds from existing data systems, metadata catalogs, and scientists contributing new and original content. ScienceBase architecture is designed to help science teams and data practitioners centralize their data and information resources to create a foundation needed for their work. ScienceBase, both original software and engineered components, is released as an open source project to promote involvement from the larger scientific programming community both inside and outside the USGS.
>>> !!! the repository is offline !!! <<< More information see: https://dknet.org/about/NURSA_Archive All NURSA-biocurated transcriptomic datasets have been preserved for data mining in SPP through an enhanced and expanded version of Transcriptomine named Ominer. To access these datasets, dkNET provides users with the information of 527 transcriptomic datasets that contain data related to nuclear receptors and nuclear receptor coregulators in the NURSA Datasets table view and redirects users to the current SPP dataset page. Once users find the specific dataset of research interest, users can download the dataset by clicking DOI and then clicking the Download Dataset button at the Signaling Pathways Project webpage. See https://www.re3data.org/repository/r3d100013650
<<<!!!<<< OFFLINE >>>!!!>>> A recent computer security audit has revealed security flaws in the legacy HapMap site that require NCBI to take it down immediately. We regret the inconvenience, but we are required to do this. That said, NCBI was planning to decommission this site in the near future anyway (although not quite so suddenly), as the 1,000 genomes (1KG) project has established itself as a research standard for population genetics and genomics. NCBI has observed a decline in usage of the HapMap dataset and website with its available resources over the past five years and it has come to the end of its useful life. The International HapMap Project is a multi-country effort to identify and catalog genetic similarities and differences in human beings. Using the information in the HapMap, researchers will be able to find genes that affect health, disease, and individual responses to medications and environmental factors. The Project is a collaboration among scientists and funding agencies from Japan, the United Kingdom, Canada, China, Nigeria, and the United States. All of the information generated by the Project will be released into the public domain. The goal of the International HapMap Project is to compare the genetic sequences of different individuals to identify chromosomal regions where genetic variants are shared. By making this information freely available, the Project will help biomedical researchers find genes involved in disease and responses to therapeutic drugs. In the initial phase of the Project, genetic data are being gathered from four populations with African, Asian, and European ancestry. Ongoing interactions with members of these populations are addressing potential ethical issues and providing valuable experience in conducting research with identified populations. Public and private organizations in six countries are participating in the International HapMap Project. Data generated by the Project can be downloaded with minimal constraints. The Project officially started with a meeting in October 2002 (https://www.genome.gov/10005336/) and is expected to take about three years.
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/
Atmosphere to Electrons (A2e) is a new, multi-year, multi-stakeholder U.S. Department of Energy (DOE) research and development initiative tasked with improving wind plant performance and mitigating risk and uncertainty to achieve substantial reduction in the cost of wind energy production. The A2e strategic vision will enable a new generation of wind plant technology, in which smart wind plants are designed to achieve optimized performance stemming from more complete knowledge of the inflow wind resource and complex flow through the wind plant.
CPES provides access to information that relates to mental disorders among the general population. Its primary goal is to collect data about the prevalence of mental disorders and their treatments in adult populations in the United States. It also allows for research related to cultural and ethnic influences on mental health. CPES combines the data collected in three different nationally representative surveys (National Comorbidity Survey Replication, National Survey of American Life, National Latino and Asian American Study).
PSI is a global health organization dedicated to improving the health of people in the developing world by focusing on serious challenges like a lack of family planning, HIV and AIDS, barriers to maternal health, and the greatest threats to children under five, including malaria, diarrhea, pneumonia and malnutrition. A hallmark of PSI is a commitment to the principle that health services and products are most effective when they are accompanied by robust communications and distribution efforts that help ensure wide acceptance and proper use. PSI works in partnership with local governments, ministries of health and local organizations to create health solutions that are built to last. We use original data to monitor and evaluate our programs, generate consumer insight, estimate the impact of our solutions, and evaluate the health of the markets we work to strengthen.
Provided by the University Libraries, KiltHub is the comprehensive institutional repository and research collaboration platform for research data and scholarly outputs produced by members of Carnegie Mellon University and their collaborators. KiltHub collects, preserves, and provides stable, long-term global open access to a wide range of research data and scholarly outputs created by faculty, staff, and student members of Carnegie Mellon University in the course of their research and teaching.
EMAGE (e-Mouse Atlas of Gene Expression) is an online biological database of gene expression data in the developing mouse (Mus musculus) embryo. The data held in EMAGE is spatially annotated to a framework of 3D mouse embryo models produced by EMAP (e-Mouse Atlas Project). These spatial annotations allow users to query EMAGE by spatial pattern as well as by gene name, anatomy term or Gene Ontology (GO) term. EMAGE is a freely available web-based resource funded by the Medical Research Council (UK) and based at the MRC Human Genetics Unit in the Institute of Genetics and Molecular Medicine, Edinburgh, UK.