A Next Generation Biological Database Management System for Search Intensive Discovery in Genomics and Proteomics

University Of Texas At Austin, Austin TX

Investigators

Abstract

Database services are an exploding concern in genomics, and are already a critical bottleneck in proteomics. In order to interpret proteomics experiments, in which measurements on hundreds or thousands of proteins are made using mass spectrometers, it is not unusual for researchers to assemble a large farm of computers to process the data produced by a single mass-spectrometer. The research funded by this proposal will result in an extendable database management system designed specifically to support complex inqueries on biological data types, including the sequence and mass spectra data central to proteomics. A central theme is (1) an focus tree-based storage structures to make the similarity searches necessary to identify proteins through database retrieval much faster and (2) the development of extensions to Structured Query Language (SQL) to enable better use of protein identification algorithms. This should lead to much faster bioinformatics algorithms, enabling rapid development of complex bioinformatics databases just as SQL has enabled development of effective programs for very large business systems.