Gene expression (GE) data provide snapshots of the cellular biology of living organisms. However, unlike sequence data, GE data only have meaning in an experimental context. Representing that context in a compact, logical way is one of the tasks of this project. Like sequence data, GE data becomes most valuable when they are pooled and become searchable. For this to happen, lab systems must exchange data with higher level databases in a compatible manner. Such compatibility would allow efficient, low-cost sharing of data, in turn encouraging distributed development of objective statistical approaches in evaluating GE data, such as dealing with differences within and between technologies. It would also help to establish baseline levels of GE under many conditions. This project is a pilot study targeted at developing a GE database system that would address such problems in that it 1. Would be freely available as an Open Source project, 2. Could exchange data in a standard format, 3. Would include all the software required to install and run the system locally, and 4. Would be scalable from lab systems to institutional repositories. As a component of the establishment of proof of concept, the project implements a pilot, publicly available installation of contributed GE data.
