Inter-sentence Relation Extraction for Associating Biological Context with Events in Biomedical Texts

Mutations in oncogenes are much more likely to lead to cancer in some tissue types than others, because some tissues express other proteins that counteract the oncogene. For example, in mice, the G12D activating mutation in K-ras causes lung tumors but not muscle-derived sarcomas, because muscle cells express two proteins (Arf and Ink4a) that cause cell division to halt when Ras is overactive. An automated event extraction system might extract the biochemical event "G12D activates mutation in K-ras", but without understanding the biological context - of whether this event occurs in lung or muscle tissue - the reader will not understand why the event does or does not lead to cancer. Biological context is not only important, it also comes in many varieties. Here we focus on biological container context, where a biological "container" may be specified at various levels of granularity, but each level serves to further specify the type of biological system in which an event might occur.