SGER: Performance Studies for Indexing Genome Sequence Databases

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The volume of sequence data grows exponentially; its analysis is a comutational challenge. The ability to analyze the data does not keep pace with production. One of the central tasks it rapid sequence comparisons. Effective strategies require algorithms that are better than linear on the size of the database in order to address the problem. In order to get an idea of how efficient various algorithms that index the database before comparing sequences are, a sensitive study of their utility against the major sequence database will be performed, considering exact and short mismatches. Indexing does improve performance so there is a possibility of identifying better ways to do it. An interdisciplinary graduate student is deeply involved in the work supported here.