Learning Statistical Models for Annotating Proteins with Function Information using Biomedical Text

Background: The BioCreative text mining evaluation investigated the application of text mining methods to the task of automatically extracting information from text in biomedical research articles. We participated in Task 2 of the evaluation. For this task, we built a system to automatically annotate a given protein with codes from the Gene Ontology (GO) using the text of an article from the biomedical literature as evidence. Methods: Our system relies on simple statistical analyses of the full text article provided. We learn n-gram models for each GO code using statistical methods and use these models to hypothesize annotations. We also learn a set of Na

• Type: Journal
• Year: 2005
• Where: BMCBI
• Authors: Soumya Ray, Mark Craven
• Keywords: BMCBI 2005, External Data Sources, N-gram Models, Text Mining