Declarative and Efficient Querying on Protein Secondary Structures

Summary

In spite of the many decades of progress in database research, surprisingly scientists in the life sciences community still struggle with inefficient and awkward tools for querying biological datasets. This work highlights a specific problem involving searching large volumes of protein datasets based on their secondary structure. In this chapter we define an intuitive query language that can be used to express queries on secondary structure and develop several algorithms for evaluating these queries. We have implemented these algorithms in Periscope, which is a native database management system that we are building for declarative querying on biological datasets. Experiments based on our implementation show that the choice of algorithms can have a significant impact on query performance. As part of the Periscope implementation, we have also developed a framework for optimizing these queries and for accurately estimating the costs of the various query evaluation plans. Our performance studies show that the proposed techniques are very efficient and can provide scientists with interactive secondary structure querying options even on large protein datasets.

Keywords

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