This document discusses using natural language processing (NLP) techniques to extract biological information from literature to help interpret large genomics datasets. The author describes developing a method to identify gene regulatory interactions by parsing Medline abstracts. This information can then be combined with data from experiments to classify protein associations and interactions. While literature provides important context, it should not be used alone. The author also intends to apply these NLP methods to full text articles to extract information from different sections like introductions and discussions.