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NIAID’s TB Portals Program is a multi-national collaboration for TB data sharing and analysis to advance TB research. As a global consortium of clinicians, scientists, and IT professionals from 40 sites in 16 countries throughout eastern Europe, Asia, and sub-Saharan Africa, the TB Portals Program is a web-based, open-access repository of multi-domain TB data and tools for its analysis. Researchers can find linked socioeconomic/geographic, clinical, laboratory, radiological, and genomic data from over 7,500 international published TB patient cases with an emphasis on drug-resistant tuberculosis.
The CPTAC Data Portal is the centralized repository for the dissemination of proteomic data collected by the Proteome Characterization Centers (PCCs) for the CPTAC program. The portal also hosts analyses of the mass spectrometry data (mapping of spectra to peptide sequences and protein identification) from the PCCs and from a CPTAC-sponsored common data analysis pipeline (CDAP).
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CanPath is Canada’s largest population health cohort and a national platform for population-level health research.It is a unique Canadian platform allowing scientists to explore the complex factors that contribute to disease. It is a deeply characterized cohort of individuals who have provided broad consent and now include two per cent of all Canadians between 30 and 74 years of age. CanPath can save researchers time — sometimes up to a decade — associated with arranging and measuring their own population samples. Researchers around the world can readily integrate CanPath data into their own studies. The standardization and harmonization of data across CanPath’s regional cohorts has been facilitated by Maelstrom Research.
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.