Milward, D., Blaschke, C., Neefs, J.-M., Ott, M.-C., Verbeeck, R., and Stubbs, A.
Proc 2nd Int Symp Semantic Mining BioMedicine. 2006; pp101-104
PMID: N/A
http://ceur-ws.org/Vol-177/poster_milward.pdf ; http://ceur-ws.org/Vol-177/
Abstract
The two text mining strategies: finding co-occurrences of biological entities within documents, and finding relationships using Natural Language Processing, are often seen as competitors. Here we adopt a flexible approach where the techniques are adapted and combined to suit the nature of the document corpus, and the specific task.
The approach was tested on three tasks relevant to cancer treatment: finding kinases associated with cancer, finding gene mutations, and finding interactions between proteins associated with cancer. The paper describes the use of entity disambiguation, cooccurrence and linguistic processing in these tasks, and provides an overview of the methodology and results.
