Murphy Lab

 Cytometry Development Workshop

 Flow Cytometry



 Carnegie Mellon University
 Computational Biology Department
 Center for Bioimage Informatics
 Biological Sciences Department
 Biomedical Engineering Department
 Machine Learning Department

The Architecture of the SLIF System

SLIF takes on-line papers and scans them for figures that contain fluorescence microscope images (FMIs). Figures typically contain multiple FMIs, to SLIF must segment these images into individual FMIs. When the FMI images are extracted, annotations for the images (for instance, names of proteins and cell-lines) are also extracted from the accompanying caption text. Protein annotation are also used to link to external databases, such as the Gene Ontology DB.

Extracted FMIs are processed to find subcellular location features (SLFs), and the resulting analyzed, annotated figures are stored in a database, which is accessible via SQL queries.

architecture of SLIF
detailed architecture of SLIF The diagram above shows the SLIF process in outline, and the diagram to the left shows the process in more detail. (Clicking on any diagram will enlarge it.) The more detailed process includes: segmentation of images into "panels"; panel classification, to find FMIs; segmentation of the caption, to find which portions of the caption apply to which panels; text-based entity extraction; matching of extracted entities to database entries; extraction of panel labels from text and figures; and alignment of the text segments to the panels. Publications that discuss these steps in detail are indicated in the detailed diagram.
The current SLIF database is populated with data from publications from The Proceedings of the National Academy of Science and Biomed Central.

Last Updated: 20 Feb 2005

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Last modified: Sun Feb 20 12:16:35 EST 2005