The application of pattern matching algorithms in bioinformatics

Molecular sequences such as DNA and proteins have a number of unique characteristics which make them computationally resource-intensive, requiring the support of massively parallel computing. However, to find the most suitable algorithm for a processing task given specific kinds of molecular data, the feasibility of a given algorithm should be measured and compared directly against other similar algorithms outside of supercomputing environment. As part of this thesis, we develop a software platform that supports search capabilities and analysis of the properties of biological data on a desktop computer. The platform supports analysis, visualization, and reporting utilities which allow users to select, test, and compare pattern matching algorithms. The platform includes a benchmark utility to evaluate the performance of pattern matching methods on molecular data. The software is based on a number of existing exact and approximate pattern matching algorithms from the literature.