Extracting Interacting Protein Pairs and Evidence Sentences by using Dependency Parsing and Machine Learning Techniques

The biomedical literature is growing rapidly. This increases the need for developing text mining techniques to automatically extract biologically important information such as protein-protein interactions from free texts. Besides identifying an interaction and the interacting pair of proteins, it is also important to extract from the full text the most relevant sentences describing that interaction. These issues were addressed in the BioCreAtIvE II (Critical Assessment for Information Extraction in Biology) challenge evaluation as sub-tasks under the protein-protein interaction extraction (PPI) task. We present our approach of using dependency parsing and machine learning techniques to identify interacting protein pairs from full text articles (Protein Interaction Pairs Sub-task 2 (IPS)) and extracting the most relevant sentences that describe their interaction (Protein Interaction Sentences Sub-task 3 (ISS)).