Extracting causal relations on HIV drug resistance from literature

Background: In HIV treatment it is critical to have up-to-date resistance data of applicable drugs since HIV has a very high rate of mutation. These data are made available through scientific publications and must be extracted manually by experts in order to be used by virologists and medical doctors. Therefore there is an urgent need for a tool that partially automates this process and is able to retrieve relations between drugs and virus mutations from literature. Results: In this work we present a novel method to extract and combine relationships between HIV drugs and mutations in viral genomes. Our extraction method is based on natural language processing (NLP) which produces grammatical relations and applies a set of rules to these relations. We applied our method to a relevant set of bstracts and obtained 2,434 extracted relations with an estimated performance of 84% for F-score. We then combined the extracted relations using logistic regression to generate resistance values for...

• Type: Journal
• Year: 2010
• Where: BMCBI
• Authors: Quoc-Chinh Bui, Breanndán Ó Nualláin, Charles A. Boucher, Peter M. A. Sloot
• Keywords: BMCBI 2010, Drug, Mutations, Resistance Data