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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.
>>> !!!!! The Cell Centered Database is no longer on serice. It has been merged with "Cell image library": https://www.re3data.org/repository/r3d100000023 !!!!! <<<<
The Fungal Genetics Stock Center has preserved and distributed strains of genetically characterized fungi since 1960. The collection includes over 20,000 accessioned strains of classical and genetically engineered mutants of key model, human, and plant pathogenic fungi. These materials are distributed as living stocks to researchers around the world.
***<<<!!!>>> *** Stated 2017-08-28: To accommodate a wider scope of ophthalmic data, we launched our new Rotterdam Ophthalmic Data Repository. Please visit http://www.rodrep.com/ for all data sets. *** The ORGIDS site will no longer be updated! ***<<<!!!>>>***Through this portal, we will make data sets available that result from our glaucoma research. This includes visual fields, various imaging modalities and other data from both glaucomatous and normal subjects.The data was acquired during more than a decade.
A collection of data at Agency for Healthcare Research and Quality (AHRQ) supporting research that helps people make more informed decisions and improves the quality of health care services. The portal contains U.S.Health Information Knowledgebase (USHIK) and Systematic Review Data Repository (SRDR) and other sources concerning cost, quality, accesibility and evaluation of healthcare and medical insurance.
Knoema is a knowledge platform. The basic idea is to connect data with analytical and presentation tools. As a result, we end with one uniformed platform for users to access, present and share data-driven content. Within Knoema, we capture most aspects of a typical data use cycle: accessing data from multiple sources, bringing relevant indicators into a common space, visualizing figures, applying analytical functions, creating a set of dashboards, and presenting the outcome.