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GigaDB primarily serves as a repository to host data and tools associated with articles published by GigaScience Press; GigaScience and GigaByte (both are online, open-access journals). GigaDB defines a dataset as a group of files (e.g., sequencing data, analyses, imaging files, software programs) that are related to and support a unit-of-work (article or study). GigaDB allows the integration of manuscript publication with supporting data and tools.
>>>!!!<<< caArray Retirement Announcement >>>!!!<<< The National Cancer Institute (NCI) Center for Biomedical Informatics and Information Technology (CBIIT) instance of the caArray database was retired on March 31st, 2015. All publicly-accessible caArray data and annotations will be archived and will remain available via FTP download https://wiki.nci.nih.gov/x/UYHeDQ and is also available at GEO http://www.ncbi.nlm.nih.gov/geo/ . >>>!!!<<< While NCI will not be able to provide technical support for the caArray software after the retirement, the source code is available on GitHub https://github.com/NCIP/caarray , and we encourage continued community development. Molecular Analysis of Brain Neoplasia (Rembrandt fine-00037) gene expression data has been loaded into ArrayExpress: http://www.ebi.ac.uk/arrayexpress/experiments/E-MTAB-3073 >>>!!!<<< caArray is an open-source, web and programmatically accessible microarray data management system that supports the annotation of microarray data using MAGE-TAB and web-based forms. Data and annotations may be kept private to the owner, shared with user-defined collaboration groups, or made public. The NCI instance of caArray hosts many cancer-related public datasets available for download.
Ag Data Commons provides access to a wide variety of open data relevant to agricultural research. We are a centralized repository for data already on the web, as well as for new data being published for the first time. While compliance with the U.S. Federal public access and open data directives is important, we aim to surpass them. Our goal is to foster innovative data re-use, integration, and visualization to support bigger, better science and policy.