Iterative Hybrid Alignment: Improving the Sensitivity of Biological Database Searches

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A grant has been awarded to Ohio State University to build a computer program that will allow researchers to find matches or matching areas in genetic sequences even when those matches are very weak. The degree of matching and the specifics of that matching among protein sequences of different organisms is central to understanding evolution and fundamental biological processes common to all organisms. As the databases of sequence data become larger and questions become more far reaching, the need for smarter search and matching algorithms becomes crucial. In this project, the PI's will develop a highly sensitive search algorithm for identifying homologies even in cases in which the actual homologies are very weak. The algorithm proposed makes much better use than current algorithms of the calculated statistical costs of insertions and deletions as they vary across the sequence. The first implementation is proposed as a redesign of PSI-BLAST but it amounts to a complete replacement of the core algorithm of that popular protein sequence search algorithm. There will also be significant changes in the peripheral functions as well. This is a new tool that will have impacts on research involving matching algorithms in general as well as within the genomics/proteomics community.