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• Provides a common location and web access to data from disparate data types including gene expression results from Next Generation Sequencing, microarray experiments, histopathological images, metabolomics data, and proteomics data, allowing for easy access by multiple collaborators and researchers located at different geographic locations. Is flexible enough to handle new and unspecified data types.
• Stores the data in one common location so that you can make biological insights that would otherwise be missed by having data in multiple locations.
• Applies the information gained from one study to multiple studies and projects.
• Allows you to search the metadata from each open access study to identify datasets of interest.
• Develops data storage and data mining modules that can be applied across studies, avoiding duplication of effort and saving costs.
• Develops and/or adopts common vocabularies, data standards, and ontologies for data representation, storage, and comparison. 

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