Informatics and Quantitative Analysis in Biological Imaging

Abstract

Biological imaging is now a quantitative technique for probing cellular structure and dynamics and is increasingly used for cell-based screens. However, the bioinformatics tools required for hypothesis-driven analysis of digital images are still immature. We are developing the Open Microscopy Environment (OME) as an informatics solution for the storage and analysis of optical microscope image data. OME aims to automate image analysis, modeling, and mining of large sets of images and specifies a flexible data model, a relational database, and an XML-encoded file standard that is usable by potentially any software tool. With this design, OME provides a first step toward biological image informatics.