Extracting Interactions from Molecular Pathways
Health and life sciences' research fields make an intensive use of graphical information to represent complex relations between biological entities, called molecular pathways. Interpretation of molecular pathway diagrams requires domain-specific knowledge to remove ambiguity. We propose a fully automatic method that detects entities and extracts their relations from diagrams. It uses image analysis and a domain-specific cognitive model and automatically produces a structured textual version of the content. Results on an annotated dataset show precision of 0.99 and recall of up to 0.85 for the detection of molecular entities and interactions.