Article
Predicting virus mutations through statistical relational learning.
BMC bioinformatics - 19 Sept 2014
Cilia Elisa, Teso Stefano, Ammendola Sergio, Lenaerts Tom, Passerini Andrea
Abstract excerpt
BACKGROUND: Viruses are typically characterized by high mutation rates, which allow them to quickly develop drug-resistant mutations. Mining relevant rules from mutation data can be extremely useful to understand the virus adaptation mechanism and to design drugs that effectively counter potentially resistant mutants. RESULTS: We propose a simple statistical relational learning approach for mutant prediction...
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