Abstract
Fluorescence microscopy is growing dramatically both in terms of technical capabilities and the volume of images generated. Online repositories have been created to provide public access to images and opportunities for joint research for many scientists1. This has reintroduced challenges faced when sequence and structure databases were being established: developing fast and effective means of searching for records (images) either by context (such as which protein is labeled) or content (such as which pattern it displays).
OMERO.searcher is an extension of the OMERO.web client that provides the ability to search for images by their content (e.g., subcellular patterns) rather than just by their annotations. It was developed by the Murphy group at Carnegie Mellon University. OMERO.searcher:
finds images whose content, as reflected by subcellular location image features, is similar to one or more query images.
- can use positive and/or negative examples.
- can be iterative, meaning it allows the user to refine the search results (a process referred to as relevance feedback).