Cancer is primarily driven by somatic mutations. It has been reported in multiple cancers that particular set of gene mutations tend not to occur concurrently in the same patient. This mutual exclusivity pattern hints at a functional relationship and can help uncover cancer-driver alterations. We recently developed a computational method, MEMNAR, to discover mutually exclusive mutation gene sets through mining negative association rules. The MEMNAR mines for negative association rules in the patient mutation data and constructs mutually exclusive gene sets based on these extracted rules with high accuracy. The PURE project aims at extending MEMNAR to noncoding mutations and discover sets that cover both noncoding and coding functional units. Students with good programming skills and algorithmic thinking capabilities with a keen interest in biology will be a good match for this project.
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