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Found 347 result(s)
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MDM-Portal (Medical Data Models) is a meta-data registry for creating, analyzing, sharing and reusing medical forms. It serves as an infrastructure for academic (non-commercial) medical research to contribute a solution to this problem. It contains forms in the system-independent CDISC Operational Data Model (ODM) format with more than 500,000 data-elements. The Portal provides numerous core data sets, common data elements or data standards, code lists and value sets. This enables researchers to view, discuss, download and export forms in most common technical formats such as PDF, CSV, Excel, SQL, SPSS, R, etc.
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The Health Atlas is an alliance of medical ontologists, medical systems biologists and clinical trials groups to design and implement a multi-functional and quality-assured atlas. It provides models, data and metadata on specific use cases from medical research projects from the partner institutions.
The SICAS Medical Image Repository is a freely accessible repository containing medical research data including medical images, surface models, clinical data, genomics data and statistical shape models. The data can freely be organized and shared on SMIR and made publicly accessible with a DOI. Dedicated data sets are organized as collections of anatomical regions (e.g Cochlea). The data can be filtered using a modular search and accessed on the web or through the SMIR API.
The Health and Medical Care Archive (HMCA) is the data archive of the Robert Wood Johnson Foundation (RWJF), the largest philanthropy devoted exclusively to health and health care in the United States. Operated by the Inter-university Consortium for Political and Social Research (ICPSR) at the University of Michigan, HMCA preserves and disseminates data collected by selected research projects funded by the Foundation and facilitates secondary analyses of the data. Our goal is to increase understanding of health and health care in the United States through secondary analysis of RWJF-supported data collections
Country
The National Population Health Data Center (NPHDC) is one of the 20 national science data center approved by the Ministry of Science and Technology and the Ministry of Finance. The Population Health Data Archive (PHDA) is developed by NPHDC relying on the Institute of Medical Information, Chinese Academy of Medical Sciences. PHDA mainly receives scientific data from science and technology projects supported by the national budget, and also collects data from other multiple sources such as medical and health institutions, research institutions and social individuals, which is oriented to the national big data strategy and the healthy China strategy. The data resources cover basic medicine, clinical medicine, public health, traditional Chinese medicine and pharmacy, pharmacy, population and reproduction. PHDA supports data collection, archiving, processing, storage, curation, verification, certification and release in the field of population health. Provide multiple types of data sharing and application services for different hierarchy users and help them find, access, interoperate and reuse the data in a safe and controlled environment. PHDA provides important support for promoting the open sharing of scientific data of population health and domestic and foreign cooperation.
GNPS is a web-based mass spectrometry ecosystem that aims to be an open-access knowledge base for community-wide organization and sharing of raw, processed or identified tandem mass (MS/MS) spectrometry data. GNPS aids in identification and discovery throughout the entire life cycle of data; from initial data acquisition/analysis to post publication.
Swiss Institute of Bioinformatics (SIB) coordinates research and education in bioinformatics throughout Switzerland and provides bioinformatics services to the national and international research community. ExPASy gives access to numerous repositories and databases of SIB. For example: array map, MetaNetX, SWISS-MODEL and World-2DPAGE, and many others see a list here http://www.expasy.org/resources
XNAT CENTRAL is a publicly accessible datasharing portal at Washinton University Medical School using XNAT software. XNAT provides neuroimaging data through a web interface and a customizable open source platform. XNAT facilitates data uploads and downloads for data sharing, processing and organization. NOTICE: Central XNAT will be decommissioned on October 15, 2023. New project creation is no longer permitted.
Launched in 2000, WormBase is an international consortium of biologists and computer scientists dedicated to providing the research community with accurate, current, accessible information concerning the genetics, genomics and biology of C. elegans and some related nematodes. In addition to their curation work, all sites have ongoing programs in bioinformatics research to develop the next generations of WormBase structure, content and accessibility
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InTOR is the institutional digital repository of the Institute of Virology, Vaccines and Sera “Torlak”. It provides open access to publications and other research outputs resulting from the projects implemented by the Institute of Virology, Vaccines and Sera “Torlak”. The software platform of the repository is adapted to the modern standards applied in the dissemination of scientific publications and is compatible with international infrastructure in this field.
CLOSER Discovery is a research tool for locating the variables that best suit your research interests and testing their robustness. Metadata repository for Longitudinal Population Studies in the United Kingdom
TCIA is a service which de-identifies and hosts a large archive of medical images of cancer accessible for public download. The data are organized as “collections”; typically patients’ imaging related by a common disease (e.g. lung cancer), image modality or type (MRI, CT, digital histopathology, etc) or research focus. Supporting data related to the images such as patient outcomes, treatment details, genomics and expert analyses are also provided when available.
SRUC is currently on a transformational journey as we move towards becoming a unique, market-led and mission diverse 21st Century rural university, driving the future needs of a dynamic, innovative and competitive rural sector in Scotland, and working with our collaborators and partners worldwide to solve the biggest global agrifood challenges. Our researchers already carry out strategic and applied research on global and local food security issues, and actively support the translation of research results into practice. Our research ethos is strongly collaborative, and we have a long history of industrial, NGO and academic partnerships locally and internationally. As well as having longstanding disciplinary strengths in several key areas, we actively promote interdisciplinary research, especially linking natural and social sciences. We have a particular interest in research that helps inform policy, with Scottish and UK Government rural affairs and environment departments and the EU as key research clients.
4TU.ResearchData, previously known as 4TU.Centre for Research Data, is a research data repository dedicated to the science, engineering and design disciplines. It offers the knowledge, experience and the tools to manage, publish and find scientific research data in a standardized, secure and well-documented manner. 4TU.ResearchData provides the research community with: Customised advice and support on research data management; A long-term repository for scientific research data; Support for current research projects; Tools to enhance reuse of research data.
Country
Australian Waterbird Surveys (AWS) is an information source of waterbird communities around Australia, based on surveys of their diversity and numbers. It relies on rigorous data collection protocols and includes more than 50 waterbird species and up to 30 years of survey data. This open source also includes the extent of flooding of thousands of wetlands observed during our surveys. As a group, waterbirds can be sentinels of the ecological health of our wetlands and rivers. We hope this free information system will help track long-term changes in the environment, provide an assessment tool for individual species, report on our national and international responsibilities and help improve the way we manage our rivers and wetlands. It has been developed with the support of research and government partners.
The Cancer Cell Line Encyclopedia project is a collaboration between the Broad Institute, and the Novartis Institutes for Biomedical Research and its Genomics Institute of the Novartis Research Foundation to conduct a detailed genetic and pharmacologic characterization of a large panel of human cancer models, to develop integrated computational analyses that link distinct pharmacologic vulnerabilities to genomic patterns and to translate cell line integrative genomics into cancer patient stratification. The CCLE provides public access to genomic data, analysis and visualization for about 1000 cell lines.
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).
The Progenetix database provides an overview of copy number abnormalities in human cancer from currently 32548 array and chromosomal Comparative Genomic Hybridization (CGH) experiments, as well as Whole Genome or Whole Exome Sequencing (WGS, WES) studies. The cancer profile data in Progenetix was curated from 1031 articles and represents 366 different cancer types, according to the International classification of Diseases in Oncology (ICD-O).
The CATH database is a hierarchical domain classification of protein structures in the Protein Data Bank. Protein structures are classified using a combination of automated and manual procedures. There are four major levels in the CATH hierarchy; Class, Architecture, Topology and Homologous superfamily.