Towards Knowledge Discovery through Automatic Inference with Text Mining in Biology and Medicine

Abstract

Field experts in biology and medicine search the literature for state-of-the-art re- sults and occasionally discover knowledge through manual inference on published causal relations. However, the results of such inference cannot be sufficiently accu- rate and/or complete, as the domain of pub- lished relations is rather huge. In this paper, we introduce an automatic inference system, BioDetective, which works on literature- mined qualitative causal information in bi- ology and medicine. BioDetective provides proofs for such qualitative causal informa- tion, and predicts the existence of new caus- al information, if there is any. The system is tested with a case study, where literature- mined information about protein regulation is utilized to come up with new knowledge.