Efficient Representation and Manipulation of Large-Scale Biological Sequence Data

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ABSTRACTStorage of biomolecular sequences, and accessing them to determine sequence homologies is central to the current revolution in bioinformatics and computational biology. Besides search tools, the large size of biological data used by some important applications underscores the need for developing efficient out-of-core algorithms. The goal of the project is to design storage structures, algorithmic techniques, and software for disk-resident sequence data, and apply it to important applications in computational biology. To achieve thisgoal, a three-pronged strategy is used: Firstly, application requirements identified in collaboration with domain experts are being used to design fundamental storage structures for sequence data. This research spans the development of efficient out-of-core algorithms for well-known in-core data structures and also the design of new data structures suitable for targeted applications. Secondly, efficient algorithms for queries on disk-resident sequence data are being developed. Finally, the out-of-core techniques developed are integrated with application software in computational genomics such as EST clustering and fragment assembly. The goal is to develop faster algorithms, reduce the exorbitant main-memory requirements, or enable solution of larger problem instances, as appropriate.The results of the research will be made accessible to computer scientistsin the form of software libraries and molecular biologists in the form of application software. Efforts are being made to integrate the results of this research into popular tools used by molecular biologists. The interdisciplinary nature of the project is providing unique training opportunities for graduate students.